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在 Amazon Bedrock 上调用 Amazon Titan Image 来生成图片
以下代码示例展示了如何在 Amazon Bedrock 上调用 Amazon Titan Image 来生成图像。
- Go
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- SDK适用于 Go V2
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注意
还有更多相关信息 GitHub。查找完整示例,学习如何在 AWS 代码示例存储库
中进行设置和运行。 使用 Amazon Titan 图像生成器创建图片。
type TitanImageRequest struct { TaskType string `json:"taskType"` TextToImageParams TextToImageParams `json:"textToImageParams"` ImageGenerationConfig ImageGenerationConfig `json:"imageGenerationConfig"` } type TextToImageParams struct { Text string `json:"text"` } type ImageGenerationConfig struct { NumberOfImages int `json:"numberOfImages"` Quality string `json:"quality"` CfgScale float64 `json:"cfgScale"` Height int `json:"height"` Width int `json:"width"` Seed int64 `json:"seed"` } type TitanImageResponse struct { Images []string `json:"images"` } // Invokes the Titan Image model to create an image using the input provided // in the request body. func (wrapper InvokeModelWrapper) InvokeTitanImage(prompt string, seed int64) (string, error) { modelId := "amazon.titan-image-generator-v1" body, err := json.Marshal(TitanImageRequest{ TaskType: "TEXT_IMAGE", TextToImageParams: TextToImageParams{ Text: prompt, }, ImageGenerationConfig: ImageGenerationConfig{ NumberOfImages: 1, Quality: "standard", CfgScale: 8.0, Height: 512, Width: 512, Seed: seed, }, }) if err != nil { log.Fatal("failed to marshal", err) } output, err := wrapper.BedrockRuntimeClient.InvokeModel(context.TODO(), &bedrockruntime.InvokeModelInput{ ModelId: aws.String(modelId), ContentType: aws.String("application/json"), Body: body, }) if err != nil { ProcessError(err, modelId) } var response TitanImageResponse if err := json.Unmarshal(output.Body, &response); err != nil { log.Fatal("failed to unmarshal", err) } base64ImageData := response.Images[0] return base64ImageData, nil }
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有关API详细信息,请参阅 “AWS SDK for Go API参考 InvokeModel
” 中的。
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- Java
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- SDK适用于 Java 2.x
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注意
还有更多相关信息 GitHub。查找完整示例,学习如何在 AWS 代码示例存储库
中进行设置和运行。 使用 Amazon Titan 图像生成器创建图片。
// Create an image with the Amazon Titan Image Generator. import org.json.JSONObject; import org.json.JSONPointer; import software.amazon.awssdk.auth.credentials.DefaultCredentialsProvider; import software.amazon.awssdk.core.SdkBytes; import software.amazon.awssdk.core.exception.SdkClientException; import software.amazon.awssdk.regions.Region; import software.amazon.awssdk.services.bedrockruntime.BedrockRuntimeClient; import java.math.BigInteger; import java.security.SecureRandom; import static com.example.bedrockruntime.libs.ImageTools.displayImage; public class InvokeModel { public static String invokeModel() { // Create a Bedrock Runtime client in the AWS Region you want to use. // Replace the DefaultCredentialsProvider with your preferred credentials provider. var client = BedrockRuntimeClient.builder() .credentialsProvider(DefaultCredentialsProvider.create()) .region(Region.US_EAST_1) .build(); // Set the model ID, e.g., Titan Image G1. var modelId = "amazon.titan-image-generator-v1"; // The InvokeModel API uses the model's native payload. // Learn more about the available inference parameters and response fields at: // https://docs.aws.amazon.com/bedrock/latest/userguide/model-parameters-titan-image.html var nativeRequestTemplate = """ { "taskType": "TEXT_IMAGE", "textToImageParams": { "text": "{{prompt}}" }, "imageGenerationConfig": { "seed": {{seed}} } }"""; // Define the prompt for the image generation. var prompt = "A stylized picture of a cute old steampunk robot"; // Get a random 31-bit seed for the image generation (max. 2,147,483,647). var seed = new BigInteger(31, new SecureRandom()); // Embed the prompt and seed in the model's native request payload. var nativeRequest = nativeRequestTemplate .replace("{{prompt}}", prompt) .replace("{{seed}}", seed.toString()); try { // Encode and send the request to the Bedrock Runtime. var response = client.invokeModel(request -> request .body(SdkBytes.fromUtf8String(nativeRequest)) .modelId(modelId) ); // Decode the response body. var responseBody = new JSONObject(response.body().asUtf8String()); // Retrieve the generated image data from the model's response. var base64ImageData = new JSONPointer("/images/0").queryFrom(responseBody).toString(); return base64ImageData; } catch (SdkClientException e) { System.err.printf("ERROR: Can't invoke '%s'. Reason: %s", modelId, e.getMessage()); throw new RuntimeException(e); } } public static void main(String[] args) { System.out.println("Generating image. This may take a few seconds..."); String base64ImageData = invokeModel(); displayImage(base64ImageData); } }
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有关API详细信息,请参阅 “AWS SDK for Java 2.x API参考 InvokeModel” 中的。
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- PHP
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- SDK for PHP
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注意
还有更多相关信息 GitHub。查找完整示例,学习如何在 AWS 代码示例存储库
中进行设置和运行。 使用 Amazon Titan 图像生成器创建图片。
public function invokeTitanImage(string $prompt, int $seed) { # The different model providers have individual request and response formats. # For the format, ranges, and default values for Titan Image models refer to: # https://docs.aws.amazon.com/bedrock/latest/userguide/model-parameters-titan-image.html $base64_image_data = ""; try { $modelId = 'amazon.titan-image-generator-v1'; $request = json_encode([ 'taskType' => 'TEXT_IMAGE', 'textToImageParams' => [ 'text' => $prompt ], 'imageGenerationConfig' => [ 'numberOfImages' => 1, 'quality' => 'standard', 'cfgScale' => 8.0, 'height' => 512, 'width' => 512, 'seed' => $seed ] ]); $result = $this->bedrockRuntimeClient->invokeModel([ 'contentType' => 'application/json', 'body' => $request, 'modelId' => $modelId, ]); $response_body = json_decode($result['body']); $base64_image_data = $response_body->images[0]; } catch (Exception $e) { echo "Error: ({$e->getCode()}) - {$e->getMessage()}\n"; } return $base64_image_data; }
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有关API详细信息,请参阅 “AWS SDK for PHP API参考 InvokeModel” 中的。
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- Python
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- SDK适用于 Python (Boto3)
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注意
还有更多相关信息 GitHub。查找完整示例,学习如何在 AWS 代码示例存储库
中进行设置和运行。 使用 Amazon Titan 图像生成器创建图片。
# Use the native inference API to create an image with Amazon Titan Image Generator import base64 import boto3 import json import os import random # Create a Bedrock Runtime client in the AWS Region of your choice. client = boto3.client("bedrock-runtime", region_name="us-east-1") # Set the model ID, e.g., Titan Image Generator G1. model_id = "amazon.titan-image-generator-v1" # Define the image generation prompt for the model. prompt = "A stylized picture of a cute old steampunk robot." # Generate a random seed. seed = random.randint(0, 2147483647) # Format the request payload using the model's native structure. native_request = { "taskType": "TEXT_IMAGE", "textToImageParams": {"text": prompt}, "imageGenerationConfig": { "numberOfImages": 1, "quality": "standard", "cfgScale": 8.0, "height": 512, "width": 512, "seed": seed, }, } # Convert the native request to JSON. request = json.dumps(native_request) # Invoke the model with the request. response = client.invoke_model(modelId=model_id, body=request) # Decode the response body. model_response = json.loads(response["body"].read()) # Extract the image data. base64_image_data = model_response["images"][0] # Save the generated image to a local folder. i, output_dir = 1, "output" if not os.path.exists(output_dir): os.makedirs(output_dir) while os.path.exists(os.path.join(output_dir, f"titan_{i}.png")): i += 1 image_data = base64.b64decode(base64_image_data) image_path = os.path.join(output_dir, f"titan_{i}.png") with open(image_path, "wb") as file: file.write(image_data) print(f"The generated image has been saved to {image_path}")
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有关API详细信息,请参阅InvokeModel中的 AWS SDKPython (Boto3) API 参考。
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有关 AWS SDK开发者指南和代码示例的完整列表,请参阅将此服务与 AWS SDK。本主题还包括有关入门的信息以及有关先前SDK版本的详细信息。
Amazon Titan Image Generator
Amazon Titan 文本