Amazon Titan Image Generator G1

Um prompt de texto para gerar a imagem deve ter <= 512 caracteres. Resoluções <= 1.408 no lado mais longo. I NegativeText (opcional) — Uma solicitação de texto para definir o que não incluir na imagem -- <= 512 caracteres. Consulte a tabela abaixo para obter uma lista completa das resoluções.

{
    "taskType": "TEXT_IMAGE",
    "textToImageParams": {
        "text": "string",      
        "negativeText": "string"
    },
    "imageGenerationConfig": {
        "numberOfImages": int,
        "height": int,
        "width": int,
        "cfgScale": float,
        "seed": int
    }
}

Os campos textToImageParams são descritos abaixo.

text (opcional): um prompt de texto para definir o que alterar dentro da máscara. Se você não incluir esse campo, o modelo tentará substituir toda a área da máscara pelo plano de fundo. Deve ter <= 512 caracteres. Texto negativo (opcional) — Uma solicitação de texto para definir o que não incluir na imagem. Deve ter <= 512 caracteres. Os limites de tamanho da imagem de entrada e da máscara de entrada são <= 1.408 no lado maior da imagem. O tamanho da saída é igual ao tamanho da entrada.

{
    "taskType": "INPAINTING",
    "inPaintingParams": {
        "image": "base64-encoded string",                         
        "text": "string",
        "negativeText": "string",        
        "maskPrompt": "string",                      
        "maskImage": "base64-encoded string",                   
    },                                                 
    "imageGenerationConfig": {
        "numberOfImages": int,
        "height": int,
        "width": int,
        "cfgScale": float
    }
}

Os campos inPaintingParams são descritos abaixo. A máscara define a parte da imagem que você deseja modificar.

text (obrigatório): um prompt de texto para definir o que alterar fora da máscara. Deve ter <= 512 caracteres. Texto negativo (opcional) — Uma solicitação de texto para definir o que não incluir na imagem. Deve ter <= 512 caracteres. Os limites de tamanho da imagem de entrada e da máscara de entrada são <= 1.408 no lado maior da imagem. O tamanho da saída é igual ao tamanho da entrada.

{
    "taskType": "OUTPAINTING",
    "outPaintingParams": {
        "text": "string",
        "negativeText": "string",        
        "image": "base64-encoded string",                         
        "maskPrompt": "string",                      
        "maskImage": "base64-encoded string",                             
        "outPaintingMode": "DEFAULT | PRECISE"                 
    },                                                 
    "imageGenerationConfig": {
        "numberOfImages": int,
        "height": int,
        "width": int,
        "cfgScale": float
    }
}

Os campos outPaintingParams estão definidos abaixo. A máscara define a área da imagem que você não deseja modificar. A geração estende perfeitamente a região que você define.

A variação da imagem permite criar variações da imagem original com base nos valores dos parâmetros. O limite de tamanho para a imagem de entrada é <= 1.408 no lado maior da imagem. Consulte a tabela abaixo para obter uma lista completa das resoluções.

{
     "taskType": "IMAGE_VARIATION",
     "imageVariationParams": {
         "text": "string",
         "negativeText": "string",
         "images": ["base64-encoded string"],
         "similarityStrength": 0.7,  # Range: 0.2 to 1.0
     },
     "imageGenerationConfig": {
         "numberOfImages": int,
         "height": int,
         "width": int,
         "cfgScale": float
     }
}

Os campos imageVariationParams estão definidos abaixo.

{
  "images": [
    "base64-encoded string", 
    ...
  ],
  "error": "string" 
}

O corpo da resposta é um objeto de streaming que contém um dos campos a seguir.

# 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 Titan Image Generator G1 model (on demand).
"""
import base64
import io
import json
import logging
import boto3
from PIL import Image

from botocore.exceptions import ClientError


class ImageError(Exception):
    "Custom exception for errors returned by Amazon Titan Image Generator G1"

    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 Titan Image Generator G1 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 Titan Image Generator G1 model %s", model_id)

    bedrock = boto3.client(service_name='bedrock-runtime')

    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 Titan Image Generator G1 model %s", model_id)

    return image_bytes


def main():
    """
    Entrypoint for Amazon Titan Image Generator G1 example.
    """

    logging.basicConfig(level=logging.INFO,
                        format="%(levelname)s: %(message)s")

    model_id = 'amazon.titan-image-generator-v1'

    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: %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 Titan Image Generator G1 model {model_id}.")


if __name__ == "__main__":
    main()

# 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 Titan Image Generator G1 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.exceptions import ClientError


class ImageError(Exception):
    "Custom exception for errors returned by Amazon Titan Image Generator G1"

    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 Titan Image Generator G1 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 Titan Image Generator G1 model %s", model_id)

    bedrock = boto3.client(service_name='bedrock-runtime')

    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 Titan Image Generator G1 model %s", model_id)

    return image_bytes


def main():
    """
    Entrypoint for Amazon Titan Image Generator G1 example.
    """
    try:
        logging.basicConfig(level=logging.INFO,
                            format="%(levelname)s: %(message)s")

        model_id = 'amazon.titan-image-generator-v1'

        # 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 Titan Image Generator G1 model {model_id}.")


if __name__ == "__main__":
    main()

# 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 Titan Image Generator G1 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.exceptions import ClientError


class ImageError(Exception):
    "Custom exception for errors returned by Amazon Titan Image Generator G1"

    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 Titan Image Generator G1 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 Titan Image Generator G1 model %s", model_id)

    bedrock = boto3.client(service_name='bedrock-runtime')

    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 Titan Image Generator G1 model %s", model_id)

    return image_bytes


def main():
    """
    Entrypoint for Amazon Titan Image Generator G1 example.
    """
    try:
        logging.basicConfig(level=logging.INFO,
                            format="%(levelname)s: %(message)s")

        model_id = 'amazon.titan-image-generator-v1'

        # 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 Titan Image Generator G1 model {model_id}.")


if __name__ == "__main__":
    main()

# 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 Titan Image Generator G1 model (on demand).
"""
import base64
import io
import json
import logging
import boto3
from PIL import Image

from botocore.exceptions import ClientError


class ImageError(Exception):
    "Custom exception for errors returned by Amazon Titan Image Generator G1"

    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 Titan Image Generator G1 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 Titan Image Generator G1 model %s", model_id)

    bedrock = boto3.client(service_name='bedrock-runtime')

    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 Titan Image Generator G1 model %s", model_id)

    return image_bytes


def main():
    """
    Entrypoint for Amazon Titan Image Generator G1 example.
    """
    try:
        logging.basicConfig(level=logging.INFO,
                            format="%(levelname)s: %(message)s")

        model_id = 'amazon.titan-image-generator-v1'

        # 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 Titan Image Generator G1 model {model_id}.")


if __name__ == "__main__":
    main()