Code examples
The following examples provide sample code for various image generation tasks.
- Text to image generation
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# Copyright Amazon.com, Inc. or its affiliates. All Rights Reserved. # SPDX-License-Identifier: Apache-2.0 """ Shows how to generate an image from a text prompt with the Amazon Nova Canvas model (on demand). """ import base64 import io import json import logging import boto3 from PIL import Image from botocore.config import Config from botocore.exceptions import ClientError class ImageError(Exception): "Custom exception for errors returned by Amazon Nova Canvas" def __init__(self, message): self.message = message logger = logging.getLogger(__name__) logging.basicConfig(level=logging.INFO) def generate_image(model_id, body): """ Generate an image using Amazon Nova Canvas model on demand. Args: model_id (str): The model ID to use. body (str) : The request body to use. Returns: image_bytes (bytes): The image generated by the model. """ logger.info( "Generating image with Amazon Nova Canvas model", model_id) bedrock = boto3.client( service_name='bedrock-runtime', config=Config(read_timeout=300) ) accept = "application/json" content_type = "application/json" response = bedrock.invoke_model( body=body, modelId=model_id, accept=accept, contentType=content_type ) response_body = json.loads(response.get("body").read()) base64_image = response_body.get("images")[0] base64_bytes = base64_image.encode('ascii') image_bytes = base64.b64decode(base64_bytes) finish_reason = response_body.get("error") if finish_reason is not None: raise ImageError(f"Image generation error. Error is {finish_reason}") logger.info( "Successfully generated image with Amazon Nova Canvas model %s", model_id) return image_bytes def main(): """ Entrypoint for Amazon Nova Canvas example. """ logging.basicConfig(level=logging.INFO, format="%(levelname)s: %(message)s") model_id = 'amazon.nova-canvas-v1:0' prompt = """A photograph of a cup of coffee from the side.""" body = json.dumps({ "taskType": "TEXT_IMAGE", "textToImageParams": { "text": prompt }, "imageGenerationConfig": { "numberOfImages": 1, "height": 1024, "width": 1024, "cfgScale": 8.0, "seed": 0 } }) try: image_bytes = generate_image(model_id=model_id, body=body) image = Image.open(io.BytesIO(image_bytes)) image.show() except ClientError as err: message = err.response["Error"]["Message"] logger.error("A client error occurred:", message) print("A client error occured: " + format(message)) except ImageError as err: logger.error(err.message) print(err.message) else: print( f"Finished generating image with Amazon Nova Canvas model {model_id}.") if __name__ == "__main__": main()
- Inpainting
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# Copyright Amazon.com, Inc. or its affiliates. All Rights Reserved. # SPDX-License-Identifier: Apache-2.0 """ Shows how to use inpainting to generate an image from a source image with the Amazon Nova Canvas model (on demand). The example uses a mask prompt to specify the area to inpaint. """ import base64 import io import json import logging import boto3 from PIL import Image from botocore.config import Config from botocore.exceptions import ClientError class ImageError(Exception): "Custom exception for errors returned by Amazon Nova Canvas" def __init__(self, message): self.message = message logger = logging.getLogger(__name__) logging.basicConfig(level=logging.INFO) def generate_image(model_id, body): """ Generate an image using Amazon Nova Canvas model on demand. Args: model_id (str): The model ID to use. body (str) : The request body to use. Returns: image_bytes (bytes): The image generated by the model. """ logger.info( "Generating image with Amazon Nova Canvas model %s", model_id) bedrock = boto3.client( service_name='bedrock-runtime', config=Config(read_timeout=300) ) accept = "application/json" content_type = "application/json" response = bedrock.invoke_model( body=body, modelId=model_id, accept=accept, contentType=content_type ) response_body = json.loads(response.get("body").read()) base64_image = response_body.get("images")[0] base64_bytes = base64_image.encode('ascii') image_bytes = base64.b64decode(base64_bytes) finish_reason = response_body.get("error") if finish_reason is not None: raise ImageError(f"Image generation error. Error is {finish_reason}") logger.info( "Successfully generated image with Amazon Nova Canvas model %s", model_id) return image_bytes def main(): """ Entrypoint for Amazon Nova Canvas example. """ try: logging.basicConfig(level=logging.INFO, format="%(levelname)s: %(message)s") model_id = 'amazon.nova-canvas-v1:0' # Read image from file and encode it as base64 string. with open("/path/to/image", "rb") as image_file: input_image = base64.b64encode(image_file.read()).decode('utf8') body = json.dumps({ "taskType": "INPAINTING", "inPaintingParams": { "text": "Modernize the windows of the house", "negativeText": "bad quality, low res", "image": input_image, "maskPrompt": "windows" }, "imageGenerationConfig": { "numberOfImages": 1, "height": 512, "width": 512, "cfgScale": 8.0 } }) image_bytes = generate_image(model_id=model_id, body=body) image = Image.open(io.BytesIO(image_bytes)) image.show() except ClientError as err: message = err.response["Error"]["Message"] logger.error("A client error occurred: %s", message) print("A client error occured: " + format(message)) except ImageError as err: logger.error(err.message) print(err.message) else: print( f"Finished generating image with Amazon Nova Canvas model {model_id}.") if __name__ == "__main__": main()
- Outpainting
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# Copyright Amazon.com, Inc. or its affiliates. All Rights Reserved. # SPDX-License-Identifier: Apache-2.0 """ Shows how to use outpainting to generate an image from a source image with the Amazon Nova Canvas model (on demand). The example uses a mask image to outpaint the original image. """ import base64 import io import json import logging import boto3 from PIL import Image from botocore.config import Config from botocore.exceptions import ClientError class ImageError(Exception): "Custom exception for errors returned by Amazon Nova Canvas" def __init__(self, message): self.message = message logger = logging.getLogger(__name__) logging.basicConfig(level=logging.INFO) def generate_image(model_id, body): """ Generate an image using Amazon Nova Canvas model on demand. Args: model_id (str): The model ID to use. body (str) : The request body to use. Returns: image_bytes (bytes): The image generated by the model. """ logger.info( "Generating image with Amazon Nova Canvas model %s", model_id) bedrock = boto3.client( service_name='bedrock-runtime', config=Config(read_timeout=300) ) accept = "application/json" content_type = "application/json" response = bedrock.invoke_model( body=body, modelId=model_id, accept=accept, contentType=content_type ) response_body = json.loads(response.get("body").read()) base64_image = response_body.get("images")[0] base64_bytes = base64_image.encode('ascii') image_bytes = base64.b64decode(base64_bytes) finish_reason = response_body.get("error") if finish_reason is not None: raise ImageError(f"Image generation error. Error is {finish_reason}") logger.info( "Successfully generated image with Amazon Nova Canvas model %s", model_id) return image_bytes def main(): """ Entrypoint for Amazon Nova Canvas example. """ try: logging.basicConfig(level=logging.INFO, format="%(levelname)s: %(message)s") model_id = 'amazon.nova-canvas-v1:0' # Read image and mask image from file and encode as base64 strings. with open("/path/to/image", "rb") as image_file: input_image = base64.b64encode(image_file.read()).decode('utf8') with open("/path/to/mask_image", "rb") as mask_image_file: input_mask_image = base64.b64encode( mask_image_file.read()).decode('utf8') body = json.dumps({ "taskType": "OUTPAINTING", "outPaintingParams": { "text": "Draw a chocolate chip cookie", "negativeText": "bad quality, low res", "image": input_image, "maskImage": input_mask_image, "outPaintingMode": "DEFAULT" }, "imageGenerationConfig": { "numberOfImages": 1, "height": 512, "width": 512, "cfgScale": 8.0 } } ) image_bytes = generate_image(model_id=model_id, body=body) image = Image.open(io.BytesIO(image_bytes)) image.show() except ClientError as err: message = err.response["Error"]["Message"] logger.error("A client error occurred: %s", message) print("A client error occured: " + format(message)) except ImageError as err: logger.error(err.message) print(err.message) else: print( f"Finished generating image with Amazon Nova Canvas model {model_id}.") if __name__ == "__main__": main()
- Image variation
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# Copyright Amazon.com, Inc. or its affiliates. All Rights Reserved. # SPDX-License-Identifier: Apache-2.0 """ Shows how to generate an image variation from a source image with the Amazon Nova Canvas model (on demand). """ import base64 import io import json import logging import boto3 from PIL import Image from botocore.config import Config from botocore.exceptions import ClientError class ImageError(Exception): "Custom exception for errors returned by Amazon Nova Canvas" def __init__(self, message): self.message = message logger = logging.getLogger(__name__) logging.basicConfig(level=logging.INFO) def generate_image(model_id, body): """ Generate an image using Amazon Nova Canvas model on demand. Args: model_id (str): The model ID to use. body (str) : The request body to use. Returns: image_bytes (bytes): The image generated by the model. """ logger.info( "Generating image with Amazon Nova Canvas model %s", model_id) bedrock = boto3.client( service_name='bedrock-runtime', config=Config(read_timeout=300) ) accept = "application/json" content_type = "application/json" response = bedrock.invoke_model( body=body, modelId=model_id, accept=accept, contentType=content_type ) response_body = json.loads(response.get("body").read()) base64_image = response_body.get("images")[0] base64_bytes = base64_image.encode('ascii') image_bytes = base64.b64decode(base64_bytes) finish_reason = response_body.get("error") if finish_reason is not None: raise ImageError(f"Image generation error. Error is {finish_reason}") logger.info( "Successfully generated image with Amazon Nova Canvas model %s", model_id) return image_bytes def main(): """ Entrypoint for Amazon Nova Canvas example. """ try: logging.basicConfig(level=logging.INFO, format="%(levelname)s: %(message)s") model_id = 'amazon.nova-canvas-v1:0' # Read image from file and encode it as base64 string. with open("/path/to/image", "rb") as image_file: input_image = base64.b64encode(image_file.read()).decode('utf8') body = json.dumps({ "taskType": "IMAGE_VARIATION", "imageVariationParams": { "text": "Modernize the house, photo-realistic, 8k, hdr", "negativeText": "bad quality, low resolution, cartoon", "images": [input_image], "similarityStrength": 0.7, # Range: 0.2 to 1.0 }, "imageGenerationConfig": { "numberOfImages": 1, "height": 512, "width": 512, "cfgScale": 8.0 } }) image_bytes = generate_image(model_id=model_id, body=body) image = Image.open(io.BytesIO(image_bytes)) image.show() except ClientError as err: message = err.response["Error"]["Message"] logger.error("A client error occurred: %s", message) print("A client error occured: " + format(message)) except ImageError as err: logger.error(err.message) print(err.message) else: print( f"Finished generating image with Amazon Nova Canvas model {model_id}.") if __name__ == "__main__": main()
- Image conditioning
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# Copyright Amazon.com, Inc. or its affiliates. All Rights Reserved. # SPDX-License-Identifier: Apache-2.0 """ Shows how to generate image conditioning from a source image with the Amazon Nova Canvas model (on demand). """ import base64 import io import json import logging import boto3 from PIL import Image from botocore.config import Config from botocore.exceptions import ClientError class ImageError(Exception): "Custom exception for errors returned by Amazon Nova Canvas" def __init__(self, message): self.message = message logger = logging.getLogger(__name__) logging.basicConfig(level=logging.INFO) def generate_image(model_id, body): """ Generate an image using Amazon Nova Canvas model on demand. Args: model_id (str): The model ID to use. body (str) : The request body to use. Returns: image_bytes (bytes): The image generated by the model. """ logger.info( "Generating image with Amazon Nova Canvas model %s", model_id) bedrock = boto3.client( service_name='bedrock-runtime', config=Config(read_timeout=300) ) accept = "application/json" content_type = "application/json" response = bedrock.invoke_model( body=body, modelId=model_id, accept=accept, contentType=content_type ) response_body = json.loads(response.get("body").read()) base64_image = response_body.get("images")[0] base64_bytes = base64_image.encode('ascii') image_bytes = base64.b64decode(base64_bytes) finish_reason = response_body.get("error") if finish_reason is not None: raise ImageError(f"Image generation error. Error is {finish_reason}") logger.info( "Successfully generated image with Amazon Nova Canvas model %s", model_id) return image_bytes def main(): """ Entrypoint for Amazon Nova Canvas example. """ try: logging.basicConfig(level=logging.INFO, format="%(levelname)s: %(message)s") model_id = 'amazon.nova-canvas-v1:0' # Read image from file and encode it as base64 string. with open("/path/to/image", "rb") as image_file: input_image = base64.b64encode(image_file.read()).decode('utf8') body = json.dumps({ "taskType": "TEXT_IMAGE", "textToImageParams": { "text": "A robot playing soccer, anime cartoon style", "negativeText": "bad quality, low res", "conditionImage": input_image, "controlMode": "CANNY_EDGE" }, "imageGenerationConfig": { "numberOfImages": 1, "height": 512, "width": 512, "cfgScale": 8.0 } }) image_bytes = generate_image(model_id=model_id, body=body) image = Image.open(io.BytesIO(image_bytes)) image.show() except ClientError as err: message = err.response["Error"]["Message"] logger.error("A client error occurred: %s", message) print("A client error occured: " + format(message)) except ImageError as err: logger.error(err.message) print(err.message) else: print( f"Finished generating image with Amazon Nova Canvas model {model_id}.") if __name__ == "__main__": main()
- Color guided content
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# Copyright Amazon.com, Inc. or its affiliates. All Rights Reserved. # SPDX-License-Identifier: Apache-2.0 """ Shows how to generate an image from a source image color palette with the Amazon Nova Canvas model (on demand). """ import base64 import io import json import logging import boto3 from PIL import Image from botocore.config import Config from botocore.exceptions import ClientError class ImageError(Exception): "Custom exception for errors returned by Amazon Nova Canvas" def __init__(self, message): self.message = message logger = logging.getLogger(__name__) logging.basicConfig(level=logging.INFO) def generate_image(model_id, body): """ Generate an image using Amazon Nova Canvas model on demand. Args: model_id (str): The model ID to use. body (str) : The request body to use. Returns: image_bytes (bytes): The image generated by the model. """ logger.info( "Generating image with Amazon Nova Canvas model %s", model_id) bedrock = boto3.client( service_name='bedrock-runtime', config=Config(read_timeout=300) ) accept = "application/json" content_type = "application/json" response = bedrock.invoke_model( body=body, modelId=model_id, accept=accept, contentType=content_type ) response_body = json.loads(response.get("body").read()) base64_image = response_body.get("images")[0] base64_bytes = base64_image.encode('ascii') image_bytes = base64.b64decode(base64_bytes) finish_reason = response_body.get("error") if finish_reason is not None: raise ImageError(f"Image generation error. Error is {finish_reason}") logger.info( "Successfully generated image with Amazon Nova Canvas model %s", model_id) return image_bytes def main(): """ Entrypoint for Amazon Nova Canvas example. """ try: logging.basicConfig(level=logging.INFO, format="%(levelname)s: %(message)s") model_id = 'amazon.nova-canvas-v1:0' # Read image from file and encode it as base64 string. with open("/path/to/image", "rb") as image_file: input_image = base64.b64encode(image_file.read()).decode('utf8') body = json.dumps({ "taskType": "COLOR_GUIDED_GENERATION", "colorGuidedGenerationParams": { "text": "digital painting of a girl, dreamy and ethereal, pink eyes, peaceful expression, ornate frilly dress, fantasy, intricate, elegant, rainbow bubbles, highly detailed, digital painting, artstation, concept art, smooth, sharp focus, illustration", "negativeText": "bad quality, low res", "referenceImage": input_image, "colors": ["#ff8080", "#ffb280", "#ffe680", "#ffe680"] }, "imageGenerationConfig": { "numberOfImages": 1, "height": 512, "width": 512, "cfgScale": 8.0 } }) image_bytes = generate_image(model_id=model_id, body=body) image = Image.open(io.BytesIO(image_bytes)) image.show() except ClientError as err: message = err.response["Error"]["Message"] logger.error("A client error occurred: %s", message) print("A client error occured: " + format(message)) except ImageError as err: logger.error(err.message) print(err.message) else: print( f"Finished generating image with Amazon Nova Canvas model {model_id}.") if __name__ == "__main__": main()
- Background removal
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# Copyright Amazon.com, Inc. or its affiliates. All Rights Reserved. # SPDX-License-Identifier: Apache-2.0 """ Shows how to generate an image with background removal with the Amazon Nova Canvas model (on demand). """ import base64 import io import json import logging import boto3 from PIL import Image from botocore.config import Config from botocore.exceptions import ClientError class ImageError(Exception): "Custom exception for errors returned by Amazon Nova Canvas" def __init__(self, message): self.message = message logger = logging.getLogger(__name__) logging.basicConfig(level=logging.INFO) def generate_image(model_id, body): """ Generate an image using Amazon Nova Canvas model on demand. Args: model_id (str): The model ID to use. body (str) : The request body to use. Returns: image_bytes (bytes): The image generated by the model. """ logger.info( "Generating image with Amazon Nova Canvas model %s", model_id) bedrock = boto3.client( service_name='bedrock-runtime', config=Config(read_timeout=300) ) accept = "application/json" content_type = "application/json" response = bedrock.invoke_model( body=body, modelId=model_id, accept=accept, contentType=content_type ) response_body = json.loads(response.get("body").read()) base64_image = response_body.get("images")[0] base64_bytes = base64_image.encode('ascii') image_bytes = base64.b64decode(base64_bytes) finish_reason = response_body.get("error") if finish_reason is not None: raise ImageError(f"Image generation error. Error is {finish_reason}") logger.info( "Successfully generated image with Amazon Nova Canvas model %s", model_id) return image_bytes def main(): """ Entrypoint for Amazon Nova Canvas example. """ try: logging.basicConfig(level=logging.INFO, format="%(levelname)s: %(message)s") model_id = 'amazon.nova-canvas-v1:0' # Read image from file and encode it as base64 string. with open("/path/to/image", "rb") as image_file: input_image = base64.b64encode(image_file.read()).decode('utf8') body = json.dumps({ "taskType": "BACKGROUND_REMOVAL", "backgroundRemovalParams": { "image": input_image, } }) image_bytes = generate_image(model_id=model_id, body=body) image = Image.open(io.BytesIO(image_bytes)) image.show() except ClientError as err: message = err.response["Error"]["Message"] logger.error("A client error occurred: %s", message) print("A client error occured: " + format(message)) except ImageError as err: logger.error(err.message) print(err.message) else: print( f"Finished generating image with Amazon Nova Canvas model {model_id}.") if __name__ == "__main__": main()
Error handling
Generating videos