Binjakët mund të gjenerojnë dhe përpunojnë imazhe në bisedë. Ju mund t'i kërkoni Binjakëve me tekst, imazhe ose një kombinim të të dyjave duke ju lejuar të krijoni, modifikoni dhe përsërisni pamjet vizuale me kontroll të paparë:
- Tekst në imazh: Gjeneroni imazhe me cilësi të lartë nga përshkrimet e tekstit të thjeshtë ose kompleks.
- Imazhi + Tekst në imazh (Redaktimi): Siguroni një imazh dhe përdorni kërkesat e tekstit për të shtuar, hequr ose modifikuar elementë, për të ndryshuar stilin ose për të rregulluar klasifikimin e ngjyrave.
- Shumë imazhe në imazh (Përbërja dhe transferimi i stilit): Përdorni imazhe të shumta hyrëse për të kompozuar një skenë të re ose për të transferuar stilin nga një imazh në tjetrin.
- Përsosja përsëritëse: Angazhohuni në një bisedë për të rafinuar në mënyrë progresive imazhin tuaj me kthesa të shumta, duke bërë rregullime të vogla derisa të jetë i përsosur.
- Paraqitja e tekstit me besueshmëri të lartë: Gjeni me saktësi imazhe që përmbajnë tekst të lexueshëm dhe të vendosur mirë, ideale për logot, diagramet dhe posterat.
Të gjitha imazhet e krijuara përfshijnë një filigran SynthID .
Gjenerimi i imazhit (tekst në imazh)
Kodi i mëposhtëm tregon se si të gjeneroni një imazh bazuar në një kërkesë përshkruese.
Python
from google import genai
from google.genai import types
from PIL import Image
from io import BytesIO
client = genai.Client()
prompt = (
"Create a picture of a nano banana dish in a fancy restaurant with a Gemini theme"
)
response = client.models.generate_content(
model="gemini-2.5-flash-image-preview",
contents=[prompt],
)
for part in response.candidates[0].content.parts:
if part.text is not None:
print(part.text)
elif part.inline_data is not None:
image = Image.open(BytesIO(part.inline_data.data))
image.save("generated_image.png")
JavaScript
import { GoogleGenAI, Modality } from "@google/genai";
import * as fs from "node:fs";
async function main() {
const ai = new GoogleGenAI({});
const prompt =
"Create a picture of a nano banana dish in a fancy restaurant with a Gemini theme";
const response = await ai.models.generateContent({
model: "gemini-2.5-flash-image-preview",
contents: prompt,
});
for (const part of response.candidates[0].content.parts) {
if (part.text) {
console.log(part.text);
} else if (part.inlineData) {
const imageData = part.inlineData.data;
const buffer = Buffer.from(imageData, "base64");
fs.writeFileSync("gemini-native-image.png", buffer);
console.log("Image saved as gemini-native-image.png");
}
}
}
main();
Shkoni
package main
import (
"context"
"fmt"
"os"
"google.golang.org/genai"
)
func main() {
ctx := context.Background()
client, err := genai.NewClient(ctx, nil)
if err != nil {
log.Fatal(err)
}
result, _ := client.Models.GenerateContent(
ctx,
"gemini-2.5-flash-image-preview",
genai.Text("Create a picture of a nano banana dish in a " +
" fancy restaurant with a Gemini theme"),
)
for _, part := range result.Candidates[0].Content.Parts {
if part.Text != "" {
fmt.Println(part.Text)
} else if part.InlineData != nil {
imageBytes := part.InlineData.Data
outputFilename := "gemini_generated_image.png"
_ = os.WriteFile(outputFilename, imageBytes, 0644)
}
}
}
PUSHIMI
curl -s -X POST
"https://generativelanguage.googleapis.com/v1beta/models/gemini-2.5-flash-image-preview:generateContent" \
-H "x-goog-api-key: $GEMINI_API_KEY" \
-H "Content-Type: application/json" \
-d '{
"contents": [{
"parts": [
{"text": "Create a picture of a nano banana dish in a fancy restaurant with a Gemini theme"}
]
}]
}' \
| grep -o '"data": "[^"]*"' \
| cut -d'"' -f4 \
| base64 --decode > gemini-native-image.png
Redaktimi i imazhit (tekst-dhe-imazh në imazh)
Kujtesë : Sigurohuni që keni të drejtat e nevojshme për çdo imazh që ngarkoni. Mos krijoni përmbajtje që cenojnë të drejtat e të tjerëve, duke përfshirë video ose imazhe që mashtrojnë, ngacmojnë ose dëmtojnë. Përdorimi juaj i këtij shërbimi gjenerues të AI i nënshtrohet Politikës sonë të Përdorimit të Ndaluar .
Shembulli i mëposhtëm tregon ngarkimin e imazheve të koduara base64. Për imazhe të shumta, ngarkesa më të mëdha dhe lloje MIME të mbështetura, kontrolloni faqen e të kuptuarit të imazhit .
Python
from google import genai
from google.genai import types
from PIL import Image
from io import BytesIO
client = genai.Client()
prompt = (
"Create a picture of my cat eating a nano-banana in a "
"fancy restaurant under the Gemini constellation",
)
image = Image.open("/path/to/cat_image.png")
response = client.models.generate_content(
model="gemini-2.5-flash-image-preview",
contents=[prompt, image],
)
for part in response.candidates[0].content.parts:
if part.text is not None:
print(part.text)
elif part.inline_data is not None:
image = Image.open(BytesIO(part.inline_data.data))
image.save("generated_image.png")
JavaScript
import { GoogleGenAI, Modality } from "@google/genai";
import * as fs from "node:fs";
async function main() {
const ai = new GoogleGenAI({});
const imagePath = "path/to/cat_image.png";
const imageData = fs.readFileSync(imagePath);
const base64Image = imageData.toString("base64");
const prompt = [
{ text: "Create a picture of my cat eating a nano-banana in a" +
"fancy restaurant under the Gemini constellation" },
{
inlineData: {
mimeType: "image/png",
data: base64Image,
},
},
];
const response = await ai.models.generateContent({
model: "gemini-2.5-flash-image-preview",
contents: prompt,
});
for (const part of response.candidates[0].content.parts) {
if (part.text) {
console.log(part.text);
} else if (part.inlineData) {
const imageData = part.inlineData.data;
const buffer = Buffer.from(imageData, "base64");
fs.writeFileSync("gemini-native-image.png", buffer);
console.log("Image saved as gemini-native-image.png");
}
}
}
main();
Shkoni
package main
import (
"context"
"fmt"
"os"
"google.golang.org/genai"
)
func main() {
ctx := context.Background()
client, err := genai.NewClient(ctx, nil)
if err != nil {
log.Fatal(err)
}
imagePath := "/path/to/cat_image.png"
imgData, _ := os.ReadFile(imagePath)
parts := []*genai.Part{
genai.NewPartFromText("Create a picture of my cat eating a nano-banana in a fancy restaurant under the Gemini constellation"),
&genai.Part{
InlineData: &genai.Blob{
MIMEType: "image/png",
Data: imgData,
},
},
}
contents := []*genai.Content{
genai.NewContentFromParts(parts, genai.RoleUser),
}
result, _ := client.Models.GenerateContent(
ctx,
"gemini-2.5-flash-image-preview",
contents,
)
for _, part := range result.Candidates[0].Content.Parts {
if part.Text != "" {
fmt.Println(part.Text)
} else if part.InlineData != nil {
imageBytes := part.InlineData.Data
outputFilename := "gemini_generated_image.png"
_ = os.WriteFile(outputFilename, imageBytes, 0644)
}
}
}
PUSHIMI
IMG_PATH=/path/to/cat_image.jpeg
if [[ "$(base64 --version 2>&1)" = *"FreeBSD"* ]]; then
B64FLAGS="--input"
else
B64FLAGS="-w0"
fi
IMG_BASE64=$(base64 "$B64FLAGS" "$IMG_PATH" 2>&1)
curl -X POST \
"https://generativelanguage.googleapis.com/v1beta/models/gemini-2.5-flash-image-preview:generateContent" \
-H "x-goog-api-key: $GEMINI_API_KEY" \
-H 'Content-Type: application/json' \
-d "{
\"contents\": [{
\"parts\":[
{\"text\": \"'Create a picture of my cat eating a nano-banana in a fancy restaurant under the Gemini constellation\"},
{
\"inline_data\": {
\"mime_type\":\"image/jpeg\",
\"data\": \"$IMG_BASE64\"
}
}
]
}]
}" \
| grep -o '"data": "[^"]*"' \
| cut -d'"' -f4 \
| base64 --decode > gemini-edited-image.png
Mënyra të tjera të gjenerimit të imazhit
Binjakët mbështet mënyra të tjera të ndërveprimit të imazhit bazuar në strukturën dhe kontekstin e shpejtë, duke përfshirë:
- Teksti në imazh(et) dhe teksti (i ndërthurur): Nxjerr imazhe me tekst përkatës.
- Shembull i kërkesës: "Krijoni një recetë të ilustruar për një paella."
- Imazhi(et) dhe teksti në imazh(et) dhe teksti (i ndërthurur) : Përdor imazhe hyrëse dhe tekst për të krijuar imazhe dhe tekst të ri të lidhur.
- Shembull i kërkesës: (Me një imazh të një dhome të mobiluar) "Cila divane me ngjyra të tjera do të funksiononin në hapësirën time? a mund ta përditësoni imazhin?"
- Redaktimi i imazhit me shumë kthesa (chat): Vazhdoni të krijoni dhe modifikoni imazhe në bisedë.
- Shembull kërkon: [ngarkoni një imazh të një makine blu.] , "Kthejeni këtë makinë në një makinë të konvertueshme.", "Tani ndryshoni ngjyrën në të verdhë."
Udhëzues nxitës dhe strategji
Zotërimi i Gemini 2.5 Flash Image Generation fillon me një parim themelor:
Përshkruani skenën, mos rendisni vetëm fjalë kyçe. Fuqia kryesore e modelit është të kuptuarit e thellë të gjuhës. Një paragraf tregimtar dhe përshkrues pothuajse gjithmonë do të prodhojë një imazh më të mirë, më koherent sesa një listë fjalësh të shkëputura.
Kërkesat për gjenerimin e imazheve
Strategjitë e mëposhtme do t'ju ndihmojnë të krijoni kërkesa efektive për të gjeneruar saktësisht imazhet që kërkoni.
1. Skena fotorealiste
Për imazhe realiste, përdorni termat e fotografisë. Përmendni këndet e kamerës, llojet e lenteve, ndriçimin dhe detajet e imta për ta drejtuar modelin drejt një rezultati fotorealist.
shabllon
A photorealistic [shot type] of [subject], [action or expression], set in
[environment]. The scene is illuminated by [lighting description], creating
a [mood] atmosphere. Captured with a [camera/lens details], emphasizing
[key textures and details]. The image should be in a [aspect ratio] format.
Prompt
A photorealistic close-up portrait of an elderly Japanese ceramicist with
deep, sun-etched wrinkles and a warm, knowing smile. He is carefully
inspecting a freshly glazed tea bowl. The setting is his rustic,
sun-drenched workshop. The scene is illuminated by soft, golden hour light
streaming through a window, highlighting the fine texture of the clay.
Captured with an 85mm portrait lens, resulting in a soft, blurred background
(bokeh). The overall mood is serene and masterful. Vertical portrait
orientation.
Python
from google import genai
from google.genai import types
from PIL import Image
from io import BytesIO
client = genai.Client()
# Generate an image from a text prompt
response = client.models.generate_content(
model="gemini-2.5-flash-image-preview",
contents="A photorealistic close-up portrait of an elderly Japanese ceramicist with deep, sun-etched wrinkles and a warm, knowing smile. He is carefully inspecting a freshly glazed tea bowl. The setting is his rustic, sun-drenched workshop with pottery wheels and shelves of clay pots in the background. The scene is illuminated by soft, golden hour light streaming through a window, highlighting the fine texture of the clay and the fabric of his apron. Captured with an 85mm portrait lens, resulting in a soft, blurred background (bokeh). The overall mood is serene and masterful.",
)
image_parts = [
part.inline_data.data
for part in response.candidates[0].content.parts
if part.inline_data
]
if image_parts:
image = Image.open(BytesIO(image_parts[0]))
image.save('photorealistic_example.png')
image.show()
JavaScript
import { GoogleGenAI, Modality } from "@google/genai";
import * as fs from "node:fs";
async function main() {
const ai = new GoogleGenAI({});
const prompt =
"A photorealistic close-up portrait of an elderly Japanese ceramicist with deep, sun-etched wrinkles and a warm, knowing smile. He is carefully inspecting a freshly glazed tea bowl. The setting is his rustic, sun-drenched workshop with pottery wheels and shelves of clay pots in the background. The scene is illuminated by soft, golden hour light streaming through a window, highlighting the fine texture of the clay and the fabric of his apron. Captured with an 85mm portrait lens, resulting in a soft, blurred background (bokeh). The overall mood is serene and masterful.";
const response = await ai.models.generateContent({
model: "gemini-2.5-flash-image-preview",
contents: prompt,
});
for (const part of response.candidates[0].content.parts) {
if (part.text) {
console.log(part.text);
} else if (part.inlineData) {
const imageData = part.inlineData.data;
const buffer = Buffer.from(imageData, "base64");
fs.writeFileSync("photorealistic_example.png", buffer);
console.log("Image saved as photorealistic_example.png");
}
}
}
main();
Shkoni
package main
import (
"context"
"fmt"
"os"
"google.golang.org/genai"
)
func main() {
ctx := context.Background()
client, err := genai.NewClient(ctx, nil)
if err != nil {
log.Fatal(err)
}
result, _ := client.Models.GenerateContent(
ctx,
"gemini-2.5-flash-image-preview",
genai.Text("A photorealistic close-up portrait of an elderly Japanese ceramicist with deep, sun-etched wrinkles and a warm, knowing smile. He is carefully inspecting a freshly glazed tea bowl. The setting is his rustic, sun-drenched workshop with pottery wheels and shelves of clay pots in the background. The scene is illuminated by soft, golden hour light streaming through a window, highlighting the fine texture of the clay and the fabric of his apron. Captured with an 85mm portrait lens, resulting in a soft, blurred background (bokeh). The overall mood is serene and masterful."),
)
for _, part := range result.Candidates[0].Content.Parts {
if part.Text != "" {
fmt.Println(part.Text)
} else if part.InlineData != nil {
imageBytes := part.InlineData.Data
outputFilename := "photorealistic_example.png"
_ = os.WriteFile(outputFilename, imageBytes, 0644)
}
}
}
PUSHIMI
curl -s -X POST
"https://generativelanguage.googleapis.com/v1beta/models/gemini-2.5-flash-image-preview:generateContent" \
-H "x-goog-api-key: $GEMINI_API_KEY" \
-H "Content-Type: application/json" \
-d '{
"contents": [{
"parts": [
{"text": "A photorealistic close-up portrait of an elderly Japanese ceramicist with deep, sun-etched wrinkles and a warm, knowing smile. He is carefully inspecting a freshly glazed tea bowl. The setting is his rustic, sun-drenched workshop with pottery wheels and shelves of clay pots in the background. The scene is illuminated by soft, golden hour light streaming through a window, highlighting the fine texture of the clay and the fabric of his apron. Captured with an 85mm portrait lens, resulting in a soft, blurred background (bokeh). The overall mood is serene and masterful."}
]
}]
}' \
| grep -o '"data": "[^"]*"' \
| cut -d'"' -f4 \
| base64 --decode > photorealistic_example.png
2. Ilustrime dhe ngjitëse të stilizuara
Për të krijuar ngjitëse, ikona ose asete, jini të qartë në lidhje me stilin dhe kërkoni një sfond transparent.
shabllon
A [style] sticker of a [subject], featuring [key characteristics] and a
[color palette]. The design should have [line style] and [shading style].
The background must be transparent.
Prompt
A kawaii-style sticker of a happy red panda wearing a tiny bamboo hat. It's
munching on a green bamboo leaf. The design features bold, clean outlines,
simple cel-shading, and a vibrant color palette. The background must be white.
Python
from google import genai
from google.genai import types
from PIL import Image
from io import BytesIO
client = genai.Client()
# Generate an image from a text prompt
response = client.models.generate_content(
model="gemini-2.5-flash-image-preview",
contents="A kawaii-style sticker of a happy red panda wearing a tiny bamboo hat. It's munching on a green bamboo leaf. The design features bold, clean outlines, simple cel-shading, and a vibrant color palette. The background must be white.",
)
image_parts = [
part.inline_data.data
for part in response.candidates[0].content.parts
if part.inline_data
]
if image_parts:
image = Image.open(BytesIO(image_parts[0]))
image.save('red_panda_sticker.png')
image.show()
JavaScript
import { GoogleGenAI, Modality } from "@google/genai";
import * as fs from "node:fs";
async function main() {
const ai = new GoogleGenAI({});
const prompt =
"A kawaii-style sticker of a happy red panda wearing a tiny bamboo hat. It's munching on a green bamboo leaf. The design features bold, clean outlines, simple cel-shading, and a vibrant color palette. The background must be white.";
const response = await ai.models.generateContent({
model: "gemini-2.5-flash-image-preview",
contents: prompt,
});
for (const part of response.candidates[0].content.parts) {
if (part.text) {
console.log(part.text);
} else if (part.inlineData) {
const imageData = part.inlineData.data;
const buffer = Buffer.from(imageData, "base64");
fs.writeFileSync("red_panda_sticker.png", buffer);
console.log("Image saved as red_panda_sticker.png");
}
}
}
main();
Shkoni
package main
import (
"context"
"fmt"
"os"
"google.golang.org/genai"
)
func main() {
ctx := context.Background()
client, err := genai.NewClient(ctx, nil)
if err != nil {
log.Fatal(err)
}
result, _ := client.Models.GenerateContent(
ctx,
"gemini-2.5-flash-image-preview",
genai.Text("A kawaii-style sticker of a happy red panda wearing a tiny bamboo hat. It's munching on a green bamboo leaf. The design features bold, clean outlines, simple cel-shading, and a vibrant color palette. The background must be white."),
)
for _, part := range result.Candidates[0].Content.Parts {
if part.Text != "" {
fmt.Println(part.Text)
} else if part.InlineData != nil {
imageBytes := part.InlineData.Data
outputFilename := "red_panda_sticker.png"
_ = os.WriteFile(outputFilename, imageBytes, 0644)
}
}
}
PUSHIMI
curl -s -X POST
"https://generativelanguage.googleapis.com/v1beta/models/gemini-2.5-flash-image-preview:generateContent" \
-H "x-goog-api-key: $GEMINI_API_KEY" \
-H "Content-Type: application/json" \
-d '{
"contents": [{
"parts": [
{"text": "A kawaii-style sticker of a happy red panda wearing a tiny bamboo hat. It'"'"'s munching on a green bamboo leaf. The design features bold, clean outlines, simple cel-shading, and a vibrant color palette. The background must be white."}
]
}]
}' \
| grep -o '"data": "[^"]*"' \
| cut -d'"' -f4 \
| base64 --decode > red_panda_sticker.png
3. Teksti i saktë në imazhe
Binjakët shkëlqejnë në përkthimin e tekstit. Jini të qartë për tekstin, stilin e shkronjave (në mënyrë përshkruese) dhe dizajnin e përgjithshëm.
shabllon
Create a [image type] for [brand/concept] with the text "[text to render]"
in a [font style]. The design should be [style description], with a
[color scheme].
Prompt
Create a modern, minimalist logo for a coffee shop called 'The Daily Grind'.
The text should be in a clean, bold, sans-serif font. The design should
feature a simple, stylized icon of a a coffee bean seamlessly integrated
with the text. The color scheme is black and white.
Python
from google import genai
from google.genai import types
from PIL import Image
from io import BytesIO
client = genai.Client()
# Generate an image from a text prompt
response = client.models.generate_content(
model="gemini-2.5-flash-image-preview",
contents="Create a modern, minimalist logo for a coffee shop called 'The Daily Grind'. The text should be in a clean, bold, sans-serif font. The design should feature a simple, stylized icon of a a coffee bean seamlessly integrated with the text. The color scheme is black and white.",
)
image_parts = [
part.inline_data.data
for part in response.candidates[0].content.parts
if part.inline_data
]
if image_parts:
image = Image.open(BytesIO(image_parts[0]))
image.save('logo_example.png')
image.show()
JavaScript
import { GoogleGenAI, Modality } from "@google/genai";
import * as fs from "node:fs";
async function main() {
const ai = new GoogleGenAI({});
const prompt =
"Create a modern, minimalist logo for a coffee shop called 'The Daily Grind'. The text should be in a clean, bold, sans-serif font. The design should feature a simple, stylized icon of a a coffee bean seamlessly integrated with the text. The color scheme is black and white.";
const response = await ai.models.generateContent({
model: "gemini-2.5-flash-image-preview",
contents: prompt,
});
for (const part of response.candidates[0].content.parts) {
if (part.text) {
console.log(part.text);
} else if (part.inlineData) {
const imageData = part.inlineData.data;
const buffer = Buffer.from(imageData, "base64");
fs.writeFileSync("logo_example.png", buffer);
console.log("Image saved as logo_example.png");
}
}
}
main();
Shkoni
package main
import (
"context"
"fmt"
"os"
"google.golang.org/genai"
)
func main() {
ctx := context.Background()
client, err := genai.NewClient(ctx, nil)
if err != nil {
log.Fatal(err)
}
result, _ := client.Models.GenerateContent(
ctx,
"gemini-2.5-flash-image-preview",
genai.Text("Create a modern, minimalist logo for a coffee shop called 'The Daily Grind'. The text should be in a clean, bold, sans-serif font. The design should feature a simple, stylized icon of a a coffee bean seamlessly integrated with the text. The color scheme is black and white."),
)
for _, part := range result.Candidates[0].Content.Parts {
if part.Text != "" {
fmt.Println(part.Text)
} else if part.InlineData != nil {
imageBytes := part.InlineData.Data
outputFilename := "logo_example.png"
_ = os.WriteFile(outputFilename, imageBytes, 0644)
}
}
}
PUSHIMI
curl -s -X POST
"https://generativelanguage.googleapis.com/v1beta/models/gemini-2.5-flash-image-preview:generateContent" \
-H "x-goog-api-key: $GEMINI_API_KEY" \
-H "Content-Type: application/json" \
-d '{
"contents": [{
"parts": [
{"text": "Create a modern, minimalist logo for a coffee shop called '"'"'The Daily Grind'"'"'. The text should be in a clean, bold, sans-serif font. The design should feature a simple, stylized icon of a a coffee bean seamlessly integrated with the text. The color scheme is black and white."}
]
}]
}' \
| grep -o '"data": "[^"]*"' \
| cut -d'"' -f4 \
| base64 --decode > logo_example.png
4. Modelet e produkteve dhe fotografitë komerciale
E përkryer për krijimin e pamjeve të pastra, profesionale të produkteve për tregtinë elektronike, reklamat ose markat.
shabllon
A high-resolution, studio-lit product photograph of a [product description]
on a [background surface/description]. The lighting is a [lighting setup,
e.g., three-point softbox setup] to [lighting purpose]. The camera angle is
a [angle type] to showcase [specific feature]. Ultra-realistic, with sharp
focus on [key detail]. [Aspect ratio].
Prompt
A high-resolution, studio-lit product photograph of a minimalist ceramic
coffee mug in matte black, presented on a polished concrete surface. The
lighting is a three-point softbox setup designed to create soft, diffused
highlights and eliminate harsh shadows. The camera angle is a slightly
elevated 45-degree shot to showcase its clean lines. Ultra-realistic, with
sharp focus on the steam rising from the coffee. Square image.
Python
from google import genai
from google.genai import types
from PIL import Image
from io import BytesIO
client = genai.Client()
# Generate an image from a text prompt
response = client.models.generate_content(
model="gemini-2.5-flash-image-preview",
contents="A high-resolution, studio-lit product photograph of a minimalist ceramic coffee mug in matte black, presented on a polished concrete surface. The lighting is a three-point softbox setup designed to create soft, diffused highlights and eliminate harsh shadows. The camera angle is a slightly elevated 45-degree shot to showcase its clean lines. Ultra-realistic, with sharp focus on the steam rising from the coffee. Square image.",
)
image_parts = [
part.inline_data.data
for part in response.candidates[0].content.parts
if part.inline_data
]
if image_parts:
image = Image.open(BytesIO(image_parts[0]))
image.save('product_mockup.png')
image.show()
JavaScript
import { GoogleGenAI, Modality } from "@google/genai";
import * as fs from "node:fs";
async function main() {
const ai = new GoogleGenAI({});
const prompt =
"A high-resolution, studio-lit product photograph of a minimalist ceramic coffee mug in matte black, presented on a polished concrete surface. The lighting is a three-point softbox setup designed to create soft, diffused highlights and eliminate harsh shadows. The camera angle is a slightly elevated 45-degree shot to showcase its clean lines. Ultra-realistic, with sharp focus on the steam rising from the coffee. Square image.";
const response = await ai.models.generateContent({
model: "gemini-2.5-flash-image-preview",
contents: prompt,
});
for (const part of response.candidates[0].content.parts) {
if (part.text) {
console.log(part.text);
} else if (part.inlineData) {
const imageData = part.inlineData.data;
const buffer = Buffer.from(imageData, "base64");
fs.writeFileSync("product_mockup.png", buffer);
console.log("Image saved as product_mockup.png");
}
}
}
main();
Shkoni
package main
import (
"context"
"fmt"
"os"
"google.golang.org/genai"
)
func main() {
ctx := context.Background()
client, err := genai.NewClient(ctx, nil)
if err != nil {
log.Fatal(err)
}
result, _ := client.Models.GenerateContent(
ctx,
"gemini-2.5-flash-image-preview",
genai.Text("A high-resolution, studio-lit product photograph of a minimalist ceramic coffee mug in matte black, presented on a polished concrete surface. The lighting is a three-point softbox setup designed to create soft, diffused highlights and eliminate harsh shadows. The camera angle is a slightly elevated 45-degree shot to showcase its clean lines. Ultra-realistic, with sharp focus on the steam rising from the coffee. Square image."),
)
for _, part := range result.Candidates[0].Content.Parts {
if part.Text != "" {
fmt.Println(part.Text)
} else if part.InlineData != nil {
imageBytes := part.InlineData.Data
outputFilename := "product_mockup.png"
_ = os.WriteFile(outputFilename, imageBytes, 0644)
}
}
}
PUSHIMI
curl -s -X POST
"https://generativelanguage.googleapis.com/v1beta/models/gemini-2.5-flash-image-preview:generateContent" \
-H "x-goog-api-key: $GEMINI_API_KEY" \
-H "Content-Type: application/json" \
-d '{
"contents": [{
"parts": [
{"text": "A high-resolution, studio-lit product photograph of a minimalist ceramic coffee mug in matte black, presented on a polished concrete surface. The lighting is a three-point softbox setup designed to create soft, diffused highlights and eliminate harsh shadows. The camera angle is a slightly elevated 45-degree shot to showcase its clean lines. Ultra-realistic, with sharp focus on the steam rising from the coffee. Square image."}
]
}]
}' \
| grep -o '"data": "[^"]*"' \
| cut -d'"' -f4 \
| base64 --decode > product_mockup.png
5. Dizajn minimalist & negativ i hapësirës
E shkëlqyeshme për krijimin e sfondeve për faqet e internetit, prezantimet ose materialet e marketingut ku teksti do të mbivendoset.
shabllon
A minimalist composition featuring a single [subject] positioned in the
[bottom-right/top-left/etc.] of the frame. The background is a vast, empty
[color] canvas, creating significant negative space. Soft, subtle lighting.
[Aspect ratio].
Prompt
A minimalist composition featuring a single, delicate red maple leaf
positioned in the bottom-right of the frame. The background is a vast, empty
off-white canvas, creating significant negative space for text. Soft,
diffused lighting from the top left. Square image.
Python
from google import genai
from google.genai import types
from PIL import Image
from io import BytesIO
client = genai.Client()
# Generate an image from a text prompt
response = client.models.generate_content(
model="gemini-2.5-flash-image-preview",
contents="A minimalist composition featuring a single, delicate red maple leaf positioned in the bottom-right of the frame. The background is a vast, empty off-white canvas, creating significant negative space for text. Soft, diffused lighting from the top left. Square image.",
)
image_parts = [
part.inline_data.data
for part in response.candidates[0].content.parts
if part.inline_data
]
if image_parts:
image = Image.open(BytesIO(image_parts[0]))
image.save('minimalist_design.png')
image.show()
JavaScript
import { GoogleGenAI, Modality } from "@google/genai";
import * as fs from "node:fs";
async function main() {
const ai = new GoogleGenAI({});
const prompt =
"A minimalist composition featuring a single, delicate red maple leaf positioned in the bottom-right of the frame. The background is a vast, empty off-white canvas, creating significant negative space for text. Soft, diffused lighting from the top left. Square image.";
const response = await ai.models.generateContent({
model: "gemini-2.5-flash-image-preview",
contents: prompt,
});
for (const part of response.candidates[0].content.parts) {
if (part.text) {
console.log(part.text);
} else if (part.inlineData) {
const imageData = part.inlineData.data;
const buffer = Buffer.from(imageData, "base64");
fs.writeFileSync("minimalist_design.png", buffer);
console.log("Image saved as minimalist_design.png");
}
}
}
main();
Shkoni
package main
import (
"context"
"fmt"
"os"
"google.golang.org/genai"
)
func main() {
ctx := context.Background()
client, err := genai.NewClient(ctx, nil)
if err != nil {
log.Fatal(err)
}
result, _ := client.Models.GenerateContent(
ctx,
"gemini-2.5-flash-image-preview",
genai.Text("A minimalist composition featuring a single, delicate red maple leaf positioned in the bottom-right of the frame. The background is a vast, empty off-white canvas, creating significant negative space for text. Soft, diffused lighting from the top left. Square image."),
)
for _, part := range result.Candidates[0].Content.Parts {
if part.Text != "" {
fmt.Println(part.Text)
} else if part.InlineData != nil {
imageBytes := part.InlineData.Data
outputFilename := "minimalist_design.png"
_ = os.WriteFile(outputFilename, imageBytes, 0644)
}
}
}
PUSHIMI
curl -s -X POST
"https://generativelanguage.googleapis.com/v1beta/models/gemini-2.5-flash-image-preview:generateContent" \
-H "x-goog-api-key: $GEMINI_API_KEY" \
-H "Content-Type: application/json" \
-d '{
"contents": [{
"parts": [
{"text": "A minimalist composition featuring a single, delicate red maple leaf positioned in the bottom-right of the frame. The background is a vast, empty off-white canvas, creating significant negative space for text. Soft, diffused lighting from the top left. Square image."}
]
}]
}' \
| grep -o '"data": "[^"]*"' \
| cut -d'"' -f4 \
| base64 --decode > minimalist_design.png
6. Arti i njëpasnjëshëm (Paneli komik / Storyboard)
Ndërtohet në konsistencën e personazheve dhe përshkrimin e skenës për të krijuar panele për tregimin vizual.
shabllon
A single comic book panel in a [art style] style. In the foreground,
[character description and action]. In the background, [setting details].
The panel has a [dialogue/caption box] with the text "[Text]". The lighting
creates a [mood] mood. [Aspect ratio].
Prompt
A single comic book panel in a gritty, noir art style with high-contrast
black and white inks. In the foreground, a detective in a trench coat stands
under a flickering streetlamp, rain soaking his shoulders. In the
background, the neon sign of a desolate bar reflects in a puddle. A caption
box at the top reads "The city was a tough place to keep secrets." The
lighting is harsh, creating a dramatic, somber mood. Landscape.
Python
from google import genai
from google.genai import types
from PIL import Image
from io import BytesIO
client = genai.Client()
# Generate an image from a text prompt
response = client.models.generate_content(
model="gemini-2.5-flash-image-preview",
contents="A single comic book panel in a gritty, noir art style with high-contrast black and white inks. In the foreground, a detective in a trench coat stands under a flickering streetlamp, rain soaking his shoulders. In the background, the neon sign of a desolate bar reflects in a puddle. A caption box at the top reads \"The city was a tough place to keep secrets.\" The lighting is harsh, creating a dramatic, somber mood. Landscape.",
)
image_parts = [
part.inline_data.data
for part in response.candidates[0].content.parts
if part.inline_data
]
if image_parts:
image = Image.open(BytesIO(image_parts[0]))
image.save('comic_panel.png')
image.show()
JavaScript
import { GoogleGenAI, Modality } from "@google/genai";
import * as fs from "node:fs";
async function main() {
const ai = new GoogleGenAI({});
const prompt =
"A single comic book panel in a gritty, noir art style with high-contrast black and white inks. In the foreground, a detective in a trench coat stands under a flickering streetlamp, rain soaking his shoulders. In the background, the neon sign of a desolate bar reflects in a puddle. A caption box at the top reads \"The city was a tough place to keep secrets.\" The lighting is harsh, creating a dramatic, somber mood. Landscape.";
const response = await ai.models.generateContent({
model: "gemini-2.5-flash-image-preview",
contents: prompt,
});
for (const part of response.candidates[0].content.parts) {
if (part.text) {
console.log(part.text);
} else if (part.inlineData) {
const imageData = part.inlineData.data;
const buffer = Buffer.from(imageData, "base64");
fs.writeFileSync("comic_panel.png", buffer);
console.log("Image saved as comic_panel.png");
}
}
}
main();
Shkoni
package main
import (
"context"
"fmt"
"os"
"google.golang.org/genai"
)
func main() {
ctx := context.Background()
client, err := genai.NewClient(ctx, nil)
if err != nil {
log.Fatal(err)
}
result, _ := client.Models.GenerateContent(
ctx,
"gemini-2.5-flash-image-preview",
genai.Text("A single comic book panel in a gritty, noir art style with high-contrast black and white inks. In the foreground, a detective in a trench coat stands under a flickering streetlamp, rain soaking his shoulders. In the background, the neon sign of a desolate bar reflects in a puddle. A caption box at the top reads \"The city was a tough place to keep secrets.\" The lighting is harsh, creating a dramatic, somber mood. Landscape."),
)
for _, part := range result.Candidates[0].Content.Parts {
if part.Text != "" {
fmt.Println(part.Text)
} else if part.InlineData != nil {
imageBytes := part.InlineData.Data
outputFilename := "comic_panel.png"
_ = os.WriteFile(outputFilename, imageBytes, 0644)
}
}
}
PUSHIMI
curl -s -X POST
"https://generativelanguage.googleapis.com/v1beta/models/gemini-2.5-flash-image-preview:generateContent" \
-H "x-goog-api-key: $GEMINI_API_KEY" \
-H "Content-Type: application/json" \
-d '{
"contents": [{
"parts": [
{"text": "A single comic book panel in a gritty, noir art style with high-contrast black and white inks. In the foreground, a detective in a trench coat stands under a flickering streetlamp, rain soaking his shoulders. In the background, the neon sign of a desolate bar reflects in a puddle. A caption box at the top reads \"The city was a tough place to keep secrets.\" The lighting is harsh, creating a dramatic, somber mood. Landscape."}
]
}]
}' \
| grep -o '"data": "[^"]*"' \
| cut -d'"' -f4 \
| base64 --decode > comic_panel.png
Kërkesat për redaktimin e imazheve
Këta shembuj tregojnë se si të siguroni imazhe së bashku me kërkesat tuaja të tekstit për redaktim, kompozim dhe transferim stili.
1. Shtimi dhe heqja e elementeve
Jepni një imazh dhe përshkruani ndryshimin tuaj. Modeli do të përputhet me stilin, ndriçimin dhe perspektivën e imazhit origjinal.
shabllon
Using the provided image of [subject], please [add/remove/modify] [element]
to/from the scene. Ensure the change is [description of how the change should
integrate].
Prompt
"Using the provided image of my cat, please add a small, knitted wizard hat
on its head. Make it look like it's sitting comfortably and matches the soft
lighting of the photo."
Python
from google import genai
from google.genai import types
from PIL import Image
from io import BytesIO
client = genai.Client()
# Base image prompt: "A photorealistic picture of a fluffy ginger cat sitting on a wooden floor, looking directly at the camera. Soft, natural light from a window."
image_input = Image.open('/path/to/your/cat_photo.png')
text_input = """Using the provided image of my cat, please add a small, knitted wizard hat on its head. Make it look like it's sitting comfortably and not falling off."""
# Generate an image from a text prompt
response = client.models.generate_content(
model="gemini-2.5-flash-image-preview",
contents=[text_input, image_input],
)
image_parts = [
part.inline_data.data
for part in response.candidates[0].content.parts
if part.inline_data
]
if image_parts:
image = Image.open(BytesIO(image_parts[0]))
image.save('cat_with_hat.png')
image.show()
JavaScript
import { GoogleGenAI, Modality } from "@google/genai";
import * as fs from "node:fs";
async function main() {
const ai = new GoogleGenAI({});
const imagePath = "/path/to/your/cat_photo.png";
const imageData = fs.readFileSync(imagePath);
const base64Image = imageData.toString("base64");
const prompt = [
{ text: "Using the provided image of my cat, please add a small, knitted wizard hat on its head. Make it look like it's sitting comfortably and not falling off." },
{
inlineData: {
mimeType: "image/png",
data: base64Image,
},
},
];
const response = await ai.models.generateContent({
model: "gemini-2.5-flash-image-preview",
contents: prompt,
});
for (const part of response.candidates[0].content.parts) {
if (part.text) {
console.log(part.text);
} else if (part.inlineData) {
const imageData = part.inlineData.data;
const buffer = Buffer.from(imageData, "base64");
fs.writeFileSync("cat_with_hat.png", buffer);
console.log("Image saved as cat_with_hat.png");
}
}
}
main();
Shkoni
package main
import (
"context"
"fmt"
"os"
"google.golang.org/genai"
)
func main() {
ctx := context.Background()
client, err := genai.NewClient(ctx, nil)
if err != nil {
log.Fatal(err)
}
imagePath := "/path/to/your/cat_photo.png"
imgData, _ := os.ReadFile(imagePath)
parts := []*genai.Part{
genai.NewPartFromText("Using the provided image of my cat, please add a small, knitted wizard hat on its head. Make it look like it's sitting comfortably and not falling off."),
&genai.Part{
InlineData: &genai.Blob{
MIMEType: "image/png",
Data: imgData,
},
},
}
contents := []*genai.Content{
genai.NewContentFromParts(parts, genai.RoleUser),
}
result, _ := client.Models.GenerateContent(
ctx,
"gemini-2.5-flash-image-preview",
contents,
)
for _, part := range result.Candidates[0].Content.Parts {
if part.Text != "" {
fmt.Println(part.Text)
} else if part.InlineData != nil {
imageBytes := part.InlineData.Data
outputFilename := "cat_with_hat.png"
_ = os.WriteFile(outputFilename, imageBytes, 0644)
}
}
}
PUSHIMI
IMG_PATH=/path/to/your/cat_photo.png
if [[ "$(base64 --version 2>&1)" = *"FreeBSD"* ]]; then
B64FLAGS="--input"
else
B64FLAGS="-w0"
fi
IMG_BASE64=$(base64 "$B64FLAGS" "$IMG_PATH" 2>&1)
curl -X POST \
"https://generativelanguage.googleapis.com/v1beta/models/gemini-2.5-flash-image-preview:generateContent" \
-H "x-goog-api-key: $GEMINI_API_KEY" \
-H 'Content-Type: application/json' \
-d "{
\"contents\": [{
\"parts\":[
{\"text\": \"Using the provided image of my cat, please add a small, knitted wizard hat on its head. Make it look like it's sitting comfortably and not falling off.\"},
{
\"inline_data\": {
\"mime_type\":\"image/png\",
\"data\": \"$IMG_BASE64\"
}
}
]
}]
}" \
| grep -o '"data": "[^"]*"' \
| cut -d'"' -f4 \
| base64 --decode > cat_with_hat.png
Input | Prodhimi |
 |  |
2. Ngjyrosje (Maskimi semantik)
Përcaktoni në bisedë një "maskë" për të redaktuar një pjesë specifike të një imazhi, duke lënë pjesën tjetër të paprekur.
shabllon
Using the provided image, change only the [specific element] to [new
element/description]. Keep everything else in the image exactly the same,
preserving the original style, lighting, and composition.
Prompt
"Using the provided image of a living room, change only the blue sofa to be
a vintage, brown leather chesterfield sofa. Keep the rest of the room,
including the pillows on the sofa and the lighting, unchanged."
Python
from google import genai
from google.genai import types
from PIL import Image
from io import BytesIO
client = genai.Client()
# Base image prompt: "A wide shot of a modern, well-lit living room with a prominent blue sofa in the center. A coffee table is in front of it and a large window is in the background."
living_room_image = Image.open('/path/to/your/living_room.png')
text_input = """Using the provided image of a living room, change only the blue sofa to be a vintage, brown leather chesterfield sofa. Keep the rest of the room, including the pillows on the sofa and the lighting, unchanged."""
# Generate an image from a text prompt
response = client.models.generate_content(
model="gemini-2.5-flash-image-preview",
contents=[living_room_image, text_input],
)
image_parts = [
part.inline_data.data
for part in response.candidates[0].content.parts
if part.inline_data
]
if image_parts:
image = Image.open(BytesIO(image_parts[0]))
image.save('living_room_edited.png')
image.show()
JavaScript
import { GoogleGenAI, Modality } from "@google/genai";
import * as fs from "node:fs";
async function main() {
const ai = new GoogleGenAI({});
const imagePath = "/path/to/your/living_room.png";
const imageData = fs.readFileSync(imagePath);
const base64Image = imageData.toString("base64");
const prompt = [
{
inlineData: {
mimeType: "image/png",
data: base64Image,
},
},
{ text: "Using the provided image of a living room, change only the blue sofa to be a vintage, brown leather chesterfield sofa. Keep the rest of the room, including the pillows on the sofa and the lighting, unchanged." },
];
const response = await ai.models.generateContent({
model: "gemini-2.5-flash-image-preview",
contents: prompt,
});
for (const part of response.candidates[0].content.parts) {
if (part.text) {
console.log(part.text);
} else if (part.inlineData) {
const imageData = part.inlineData.data;
const buffer = Buffer.from(imageData, "base64");
fs.writeFileSync("living_room_edited.png", buffer);
console.log("Image saved as living_room_edited.png");
}
}
}
main();
Shkoni
package main
import (
"context"
"fmt"
"os"
"google.golang.org/genai"
)
func main() {
ctx := context.Background()
client, err := genai.NewClient(ctx, nil)
if err != nil {
log.Fatal(err)
}
imagePath := "/path/to/your/living_room.png"
imgData, _ := os.ReadFile(imagePath)
parts := []*genai.Part{
&genai.Part{
InlineData: &genai.Blob{
MIMEType: "image/png",
Data: imgData,
},
},
genai.NewPartFromText("Using the provided image of a living room, change only the blue sofa to be a vintage, brown leather chesterfield sofa. Keep the rest of the room, including the pillows on the sofa and the lighting, unchanged."),
}
contents := []*genai.Content{
genai.NewContentFromParts(parts, genai.RoleUser),
}
result, _ := client.Models.GenerateContent(
ctx,
"gemini-2.5-flash-image-preview",
contents,
)
for _, part := range result.Candidates[0].Content.Parts {
if part.Text != "" {
fmt.Println(part.Text)
} else if part.InlineData != nil {
imageBytes := part.InlineData.Data
outputFilename := "living_room_edited.png"
_ = os.WriteFile(outputFilename, imageBytes, 0644)
}
}
}
PUSHIMI
IMG_PATH=/path/to/your/living_room.png
if [[ "$(base64 --version 2>&1)" = *"FreeBSD"* ]]; then
B64FLAGS="--input"
else
B64FLAGS="-w0"
fi
IMG_BASE64=$(base64 "$B64FLAGS" "$IMG_PATH" 2>&1)
curl -X POST \
"https://generativelanguage.googleapis.com/v1beta/models/gemini-2.5-flash-image-preview:generateContent" \
-H "x-goog-api-key: $GEMINI_API_KEY" \
-H 'Content-Type: application/json' \
-d "{
\"contents\": [{
\"parts\":[
{
\"inline_data\": {
\"mime_type\":\"image/png\",
\"data\": \"$IMG_BASE64\"
}
},
{\"text\": \"Using the provided image of a living room, change only the blue sofa to be a vintage, brown leather chesterfield sofa. Keep the rest of the room, including the pillows on the sofa and the lighting, unchanged.\"}
]
}]
}" \
| grep -o '"data": "[^"]*"' \
| cut -d'"' -f4 \
| base64 --decode > living_room_edited.png
Input | Prodhimi |
 |  |
3. Transferimi i stilit
Jepni një imazh dhe kërkojini modeles të rikrijojë përmbajtjen e tij në një stil tjetër artistik.
shabllon
Transform the provided photograph of [subject] into the artistic style of [artist/art style]. Preserve the original composition but render it with [description of stylistic elements].
Prompt
"Transform the provided photograph of a modern city street at night into the artistic style of Vincent van Gogh's 'Starry Night'. Preserve the original composition of buildings and cars, but render all elements with swirling, impasto brushstrokes and a dramatic palette of deep blues and bright yellows."
Python
from google import genai
from google.genai import types
from PIL import Image
from io import BytesIO
client = genai.Client()
# Base image prompt: "A photorealistic, high-resolution photograph of a busy city street in New York at night, with bright neon signs, yellow taxis, and tall skyscrapers."
city_image = Image.open('/path/to/your/city.png')
text_input = """Transform the provided photograph of a modern city street at night into the artistic style of Vincent van Gogh's 'Starry Night'. Preserve the original composition of buildings and cars, but render all elements with swirling, impasto brushstrokes and a dramatic palette of deep blues and bright yellows."""
# Generate an image from a text prompt
response = client.models.generate_content(
model="gemini-2.5-flash-image-preview",
contents=[city_image, text_input],
)
image_parts = [
part.inline_data.data
for part in response.candidates[0].content.parts
if part.inline_data
]
if image_parts:
image = Image.open(BytesIO(image_parts[0]))
image.save('city_style_transfer.png')
image.show()
JavaScript
import { GoogleGenAI, Modality } from "@google/genai";
import * as fs from "node:fs";
async function main() {
const ai = new GoogleGenAI({});
const imagePath = "/path/to/your/city.png";
const imageData = fs.readFileSync(imagePath);
const base64Image = imageData.toString("base64");
const prompt = [
{
inlineData: {
mimeType: "image/png",
data: base64Image,
},
},
{ text: "Transform the provided photograph of a modern city street at night into the artistic style of Vincent van Gogh's 'Starry Night'. Preserve the original composition of buildings and cars, but render all elements with swirling, impasto brushstrokes and a dramatic palette of deep blues and bright yellows." },
];
const response = await ai.models.generateContent({
model: "gemini-2.5-flash-image-preview",
contents: prompt,
});
for (const part of response.candidates[0].content.parts) {
if (part.text) {
console.log(part.text);
} else if (part.inlineData) {
const imageData = part.inlineData.data;
const buffer = Buffer.from(imageData, "base64");
fs.writeFileSync("city_style_transfer.png", buffer);
console.log("Image saved as city_style_transfer.png");
}
}
}
main();
Shkoni
package main
import (
"context"
"fmt"
"os"
"google.golang.org/genai"
)
func main() {
ctx := context.Background()
client, err := genai.NewClient(ctx, nil)
if err != nil {
log.Fatal(err)
}
imagePath := "/path/to/your/city.png"
imgData, _ := os.ReadFile(imagePath)
parts := []*genai.Part{
&genai.Part{
InlineData: &genai.Blob{
MIMEType: "image/png",
Data: imgData,
},
},
genai.NewPartFromText("Transform the provided photograph of a modern city street at night into the artistic style of Vincent van Gogh's 'Starry Night'. Preserve the original composition of buildings and cars, but render all elements with swirling, impasto brushstrokes and a dramatic palette of deep blues and bright yellows."),
}
contents := []*genai.Content{
genai.NewContentFromParts(parts, genai.RoleUser),
}
result, _ := client.Models.GenerateContent(
ctx,
"gemini-2.5-flash-image-preview",
contents,
)
for _, part := range result.Candidates[0].Content.Parts {
if part.Text != "" {
fmt.Println(part.Text)
} else if part.InlineData != nil {
imageBytes := part.InlineData.Data
outputFilename := "city_style_transfer.png"
_ = os.WriteFile(outputFilename, imageBytes, 0644)
}
}
}
PUSHIMI
IMG_PATH=/path/to/your/city.png
if [[ "$(base64 --version 2>&1)" = *"FreeBSD"* ]]; then
B64FLAGS="--input"
else
B64FLAGS="-w0"
fi
IMG_BASE64=$(base64 "$B64FLAGS" "$IMG_PATH" 2>&1)
curl -X POST \
"https://generativelanguage.googleapis.com/v1beta/models/gemini-2.5-flash-image-preview:generateContent" \
-H "x-goog-api-key: $GEMINI_API_KEY" \
-H 'Content-Type: application/json' \
-d "{
\"contents\": [{
\"parts\":[
{
\"inline_data\": {
\"mime_type\":\"image/png\",
\"data\": \"$IMG_BASE64\"
}
},
{\"text\": \"Transform the provided photograph of a modern city street at night into the artistic style of Vincent van Gogh's 'Starry Night'. Preserve the original composition of buildings and cars, but render all elements with swirling, impasto brushstrokes and a dramatic palette of deep blues and bright yellows.\"}
]
}]
}" \
| grep -o '"data": "[^"]*"' \
| cut -d'"' -f4 \
| base64 --decode > city_style_transfer.png
Input | Prodhimi |
 |  |
4. Kompozim i avancuar: Kombinimi i imazheve të shumta
Siguroni imazhe të shumta si kontekst për të krijuar një skenë të re, të përbërë. Kjo është e përkryer për modele produktesh ose kolazhe krijuese.
shabllon
Create a new image by combining the elements from the provided images. Take
the [element from image 1] and place it with/on the [element from image 2].
The final image should be a [description of the final scene].
Prompt
"Create a professional e-commerce fashion photo. Take the blue floral dress
from the first image and let the woman from the second image wear it.
Generate a realistic, full-body shot of the woman wearing the dress, with
the lighting and shadows adjusted to match the outdoor environment."
Python
from google import genai
from google.genai import types
from PIL import Image
from io import BytesIO
client = genai.Client()
# Base image prompts:
# 1. Dress: "A professionally shot photo of a blue floral summer dress on a plain white background, ghost mannequin style."
# 2. Model: "Full-body shot of a woman with her hair in a bun, smiling, standing against a neutral grey studio background."
dress_image = Image.open('/path/to/your/dress.png')
model_image = Image.open('/path/to/your/model.png')
text_input = """Create a professional e-commerce fashion photo. Take the blue floral dress from the first image and let the woman from the second image wear it. Generate a realistic, full-body shot of the woman wearing the dress, with the lighting and shadows adjusted to match the outdoor environment."""
# Generate an image from a text prompt
response = client.models.generate_content(
model="gemini-2.5-flash-image-preview",
contents=[dress_image, model_image, text_input],
)
image_parts = [
part.inline_data.data
for part in response.candidates[0].content.parts
if part.inline_data
]
if image_parts:
image = Image.open(BytesIO(image_parts[0]))
image.save('fashion_ecommerce_shot.png')
image.show()
JavaScript
import { GoogleGenAI, Modality } from "@google/genai";
import * as fs from "node:fs";
async function main() {
const ai = new GoogleGenAI({});
const imagePath1 = "/path/to/your/dress.png";
const imageData1 = fs.readFileSync(imagePath1);
const base64Image1 = imageData1.toString("base64");
const imagePath2 = "/path/to/your/model.png";
const imageData2 = fs.readFileSync(imagePath2);
const base64Image2 = imageData2.toString("base64");
const prompt = [
{
inlineData: {
mimeType: "image/png",
data: base64Image1,
},
},
{
inlineData: {
mimeType: "image/png",
data: base64Image2,
},
},
{ text: "Create a professional e-commerce fashion photo. Take the blue floral dress from the first image and let the woman from the second image wear it. Generate a realistic, full-body shot of the woman wearing the dress, with the lighting and shadows adjusted to match the outdoor environment." },
];
const response = await ai.models.generateContent({
model: "gemini-2.5-flash-image-preview",
contents: prompt,
});
for (const part of response.candidates[0].content.parts) {
if (part.text) {
console.log(part.text);
} else if (part.inlineData) {
const imageData = part.inlineData.data;
const buffer = Buffer.from(imageData, "base64");
fs.writeFileSync("fashion_ecommerce_shot.png", buffer);
console.log("Image saved as fashion_ecommerce_shot.png");
}
}
}
main();
Shkoni
package main
import (
"context"
"fmt"
"os"
"google.golang.org/genai"
)
func main() {
ctx := context.Background()
client, err := genai.NewClient(ctx, nil)
if err != nil {
log.Fatal(err)
}
imgData1, _ := os.ReadFile("/path/to/your/dress.png")
imgData2, _ := os.ReadFile("/path/to/your/model.png")
parts := []*genai.Part{
&genai.Part{
InlineData: &genai.Blob{
MIMEType: "image/png",
Data: imgData1,
},
},
&genai.Part{
InlineData: &genai.Blob{
MIMEType: "image/png",
Data: imgData2,
},
},
genai.NewPartFromText("Create a professional e-commerce fashion photo. Take the blue floral dress from the first image and let the woman from the second image wear it. Generate a realistic, full-body shot of the woman wearing the dress, with the lighting and shadows adjusted to match the outdoor environment."),
}
contents := []*genai.Content{
genai.NewContentFromParts(parts, genai.RoleUser),
}
result, _ := client.Models.GenerateContent(
ctx,
"gemini-2.5-flash-image-preview",
contents,
)
for _, part := range result.Candidates[0].Content.Parts {
if part.Text != "" {
fmt.Println(part.Text)
} else if part.InlineData != nil {
imageBytes := part.InlineData.Data
outputFilename := "fashion_ecommerce_shot.png"
_ = os.WriteFile(outputFilename, imageBytes, 0644)
}
}
}
PUSHIMI
IMG_PATH1=/path/to/your/dress.png
IMG_PATH2=/path/to/your/model.png
if [[ "$(base64 --version 2>&1)" = *"FreeBSD"* ]]; then
B64FLAGS="--input"
else
B64FLAGS="-w0"
fi
IMG1_BASE64=$(base64 "$B64FLAGS" "$IMG_PATH1" 2>&1)
IMG2_BASE64=$(base64 "$B64FLAGS" "$IMG_PATH2" 2>&1)
curl -X POST \
"https://generativelanguage.googleapis.com/v1beta/models/gemini-2.5-flash-image-preview:generateContent" \
-H "x-goog-api-key: $GEMINI_API_KEY" \
-H 'Content-Type: application/json' \
-d "{
\"contents\": [{
\"parts\":[
{
\"inline_data\": {
\"mime_type\":\"image/png\",
\"data\": \"$IMG1_BASE64\"
}
},
{
\"inline_data\": {
\"mime_type\":\"image/png\",
\"data\": \"$IMG2_BASE64\"
}
},
{\"text\": \"Create a professional e-commerce fashion photo. Take the blue floral dress from the first image and let the woman from the second image wear it. Generate a realistic, full-body shot of the woman wearing the dress, with the lighting and shadows adjusted to match the outdoor environment.\"}
]
}]
}" \
| grep -o '"data": "[^"]*"' \
| cut -d'"' -f4 \
| base64 --decode > fashion_ecommerce_shot.png
Hyrja 1 | Hyrja 2 | Prodhimi |
 |  |  |
5. Ruajtja e detajeve me besnikëri të lartë
Për t'u siguruar që detajet kritike (si një fytyrë ose logo) të ruhen gjatë një modifikimi, përshkruani ato në detaje së bashku me kërkesën tuaj për modifikim.
shabllon
Using the provided images, place [element from image 2] onto [element from
image 1]. Ensure that the features of [element from image 1] remain
completely unchanged. The added element should [description of how the
element should integrate].
Prompt
"Take the first image of the woman with brown hair, blue eyes, and a neutral
expression. Add the logo from the second image onto her black t-shirt.
Ensure the woman's face and features remain completely unchanged. The logo
should look like it's naturally printed on the fabric, following the folds
of the shirt."
Python
from google import genai
from google.genai import types
from PIL import Image
from io import BytesIO
client = genai.Client()
# Base image prompts:
# 1. Woman: "A professional headshot of a woman with brown hair and blue eyes, wearing a plain black t-shirt, against a neutral studio background."
# 2. Logo: "A simple, modern logo with the letters 'G' and 'A' in a white circle."
woman_image = Image.open('/path/to/your/woman.png')
logo_image = Image.open('/path/to/your/logo.png')
text_input = """Take the first image of the woman with brown hair, blue eyes, and a neutral expression. Add the logo from the second image onto her black t-shirt. Ensure the woman's face and features remain completely unchanged. The logo should look like it's naturally printed on the fabric, following the folds of the shirt."""
# Generate an image from a text prompt
response = client.models.generate_content(
model="gemini-2.5-flash-image-preview",
contents=[woman_image, logo_image, text_input],
)
image_parts = [
part.inline_data.data
for part in response.candidates[0].content.parts
if part.inline_data
]
if image_parts:
image = Image.open(BytesIO(image_parts[0]))
image.save('woman_with_logo.png')
image.show()
JavaScript
import { GoogleGenAI, Modality } from "@google/genai";
import * as fs from "node:fs";
async function main() {
const ai = new GoogleGenAI({});
const imagePath1 = "/path/to/your/woman.png";
const imageData1 = fs.readFileSync(imagePath1);
const base64Image1 = imageData1.toString("base64");
const imagePath2 = "/path/to/your/logo.png";
const imageData2 = fs.readFileSync(imagePath2);
const base64Image2 = imageData2.toString("base64");
const prompt = [
{
inlineData: {
mimeType: "image/png",
data: base64Image1,
},
},
{
inlineData: {
mimeType: "image/png",
data: base64Image2,
},
},
{ text: "Take the first image of the woman with brown hair, blue eyes, and a neutral expression. Add the logo from the second image onto her black t-shirt. Ensure the woman's face and features remain completely unchanged. The logo should look like it's naturally printed on the fabric, following the folds of the shirt." },
];
const response = await ai.models.generateContent({
model: "gemini-2.5-flash-image-preview",
contents: prompt,
});
for (const part of response.candidates[0].content.parts) {
if (part.text) {
console.log(part.text);
} else if (part.inlineData) {
const imageData = part.inlineData.data;
const buffer = Buffer.from(imageData, "base64");
fs.writeFileSync("woman_with_logo.png", buffer);
console.log("Image saved as woman_with_logo.png");
}
}
}
main();
Shkoni
package main
import (
"context"
"fmt"
"os"
"google.golang.org/genai"
)
func main() {
ctx := context.Background()
client, err := genai.NewClient(ctx, nil)
if err != nil {
log.Fatal(err)
}
imgData1, _ := os.ReadFile("/path/to/your/woman.png")
imgData2, _ := os.ReadFile("/path/to/your/logo.png")
parts := []*genai.Part{
&genai.Part{
InlineData: &genai.Blob{
MIMEType: "image/png",
Data: imgData1,
},
},
&genai.Part{
InlineData: &genai.Blob{
MIMEType: "image/png",
Data: imgData2,
},
},
genai.NewPartFromText("Take the first image of the woman with brown hair, blue eyes, and a neutral expression. Add the logo from the second image onto her black t-shirt. Ensure the woman's face and features remain completely unchanged. The logo should look like it's naturally printed on the fabric, following the folds of the shirt."),
}
contents := []*genai.Content{
genai.NewContentFromParts(parts, genai.RoleUser),
}
result, _ := client.Models.GenerateContent(
ctx,
"gemini-2.5-flash-image-preview",
contents,
)
for _, part := range result.Candidates[0].Content.Parts {
if part.Text != "" {
fmt.Println(part.Text)
} else if part.InlineData != nil {
imageBytes := part.InlineData.Data
outputFilename := "woman_with_logo.png"
_ = os.WriteFile(outputFilename, imageBytes, 0644)
}
}
}
PUSHIMI
IMG_PATH1=/path/to/your/woman.png
IMG_PATH2=/path/to/your/logo.png
if [[ "$(base64 --version 2>&1)" = *"FreeBSD"* ]]; then
B64FLAGS="--input"
else
B64FLAGS="-w0"
fi
IMG1_BASE64=$(base64 "$B64FLAGS" "$IMG_PATH1" 2>&1)
IMG2_BASE64=$(base64 "$B64FLAGS" "$IMG_PATH2" 2>&1)
curl -X POST \
"https://generativelanguage.googleapis.com/v1beta/models/gemini-2.5-flash-image-preview:generateContent" \
-H "x-goog-api-key: $GEMINI_API_KEY" \
-H 'Content-Type: application/json' \
-d "{
\"contents\": [{
\"parts\":[
{
\"inline_data\": {
\"mime_type\":\"image/png\",
\"data\": \"$IMG1_BASE64\"
}
},
{
\"inline_data\": {
\"mime_type\":\"image/png\",
\"data\": \"$IMG2_BASE64\"
}
},
{\"text\": \"Take the first image of the woman with brown hair, blue eyes, and a neutral expression. Add the logo from the second image onto her black t-shirt. Ensure the woman's face and features remain completely unchanged. The logo should look like it's naturally printed on the fabric, following the folds of the shirt.\"}
]
}]
}" \
| grep -o '"data": "[^"]*"' \
| cut -d'"' -f4 \
| base64 --decode > woman_with_logo.png
Hyrja 1 | Hyrja 2 | Prodhimi |
 |  |  |
Praktikat më të mira
Për t'i ngritur rezultatet tuaja nga të mira në të shkëlqyera, inkorporoni këto strategji profesionale në rrjedhën tuaj të punës.
- Jini Hiper-Specifik: Sa më shumë detaje të jepni, aq më shumë kontroll keni. Në vend të "forca të blinduara fantazi", përshkruajeni atë: "armë të zbukuruar me pjatë kukudhi, të gdhendura me modele gjethesh argjendi, me një jakë të lartë dhe kavanoza në formë si krahë skifteri".
- Jepni kontekstin dhe qëllimin: Shpjegoni qëllimin e imazhit. Kuptimi i kontekstit nga modeli do të ndikojë në rezultatin përfundimtar. Për shembull, "Krijo një logo për një markë të nivelit të lartë dhe minimalist të kujdesit të lëkurës" do të japë rezultate më të mira sesa thjesht "Krijo një logo".
- Përsëriteni dhe përsosni: Mos prisni një imazh të përsosur në provën e parë. Përdorni natyrën bisedore të modelit për të bërë ndryshime të vogla. Ndiq me kërkesat si: "Kjo është e mrekullueshme, por a mund ta bëni ndriçimin pak më të ngrohtë?" ose "Mbaje gjithçka njësoj, por ndrysho shprehjen e personazhit për të qenë më serioz".
- Përdorni udhëzimet hap pas hapi: Për skena komplekse me shumë elementë, ndajeni kërkesën tuaj në hapa. "Së pari, krijoni një sfond të një pylli të qetë dhe të mjegullt në agim. Më pas, në plan të parë, shtoni një altar të lashtë prej guri të mbuluar me myshk. Së fundi, vendosni një shpatë të vetme, të ndezur në majë të altarit."
- Përdorni "Kërkesat Semantike Negative": Në vend që të thoni "pa makina", përshkruani skenën e dëshiruar pozitivisht: "një rrugë e zbrazët, e shkretë pa shenja trafiku".
- Kontrolloni kamerën: Përdorni gjuhë fotografike dhe kinematografike për të kontrolluar përbërjen. Terma si
wide-angle shot,macro shot,low-angle perspective.
Kufizimet
- Për performancën më të mirë, përdorni gjuhët e mëposhtme: EN, es-MX, ja-JP, zh-CN, hi-IN.
- Gjenerimi i imazhit nuk mbështet hyrjet audio ose video.
- Modeli nuk do të ndjekë gjithmonë numrin e saktë të daljeve të imazhit që përdoruesi ka kërkuar në mënyrë eksplicite.
- Modeli funksionon më së miri me deri në 3 imazhe si hyrje.
- Kur krijoni tekst për një imazh, Binjakët funksionojnë më mirë nëse së pari krijoni tekstin dhe më pas kërkoni një imazh me tekstin.
- Ngarkimi i imazheve të fëmijëve nuk mbështetet aktualisht në EEA, CH dhe MB.
- Të gjitha imazhet e krijuara përfshijnë një filigran SynthID .
Kur të përdorni Imagen
Përveç përdorimit të aftësive të integruara të gjenerimit të imazheve të Gemini, ju mund të përdorni gjithashtu Imagen , modelin tonë të specializuar të gjenerimit të imazheve, përmes Gemini API.
| atribut | Imazhi | Imazhi amtare i Binjakëve |
|---|---|---|
| Pikat e forta | Modeli më i aftë për gjenerimin e imazheve deri më sot. Rekomandohet për imazhe fotorealiste, qartësi më të mprehtë, drejtshkrim dhe tipografi të përmirësuar. | Rekomandimi i parazgjedhur. Fleksibilitet i pashembullt, kuptim kontekstual dhe redaktim i thjeshtë, pa maska. E aftë unike për redaktimin e bisedave me shumë kthesa. |
| Disponueshmëria | Në përgjithësi në dispozicion | Pamja paraprake (lejohet përdorimi i prodhimit) |
| Vonesa | E ulët . Optimizuar për performancë pothuajse në kohë reale. | Më e lartë. Kërkohet më shumë llogaritje për aftësitë e tij të avancuara. |
| Kostoja | Me kosto efektive për detyra të specializuara. 0,02 $/imazh në 0,12 $/imazh | Çmimi i bazuar në token. 30 dollarë për 1 milion argumente për daljen e imazhit (dalja e imazhit të tokenizuar me 1290 argumente për imazh të sheshtë, deri në 1024x1024 px) |
| Detyrat e rekomanduara |
|
|
Imagen 4 duhet të jetë modeli juaj i preferuar që fillon të gjenerojë imazhe me Imagen. Zgjidhni Imagen 4 Ultra për përdorime të avancuara ose kur keni nevojë për cilësinë më të mirë të imazhit (vini re se mund të gjenerojë vetëm një imazh në të njëjtën kohë).
Çfarë është më pas
- Gjeni më shumë shembuj dhe shembuj kodesh në udhëzuesin e librit të gatimit .
- Shikoni udhëzuesin Veo për të mësuar se si të gjeneroni video me Gemini API.
- Për të mësuar më shumë rreth modeleve të Binjakëve, shihni modelet e Binjakëve .