- Text-to-image generation
-
# 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()
- Inpainting
-
# 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()
- Outpainting
-
# 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()
- Image variation
-
# 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()
- Image conditioning (V2 only)
-
# 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 Titan Image Generator G1 V2 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 V2"
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 V2 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 V2 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 V2 model %s", model_id)
return image_bytes
def main():
"""
Entrypoint for Amazon Titan Image Generator V2 example.
"""
try:
logging.basicConfig(level=logging.INFO,
format="%(levelname)s: %(message)s")
model_id = 'amazon.titan-image-generator-v2:0'
# 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 Titan Image Generator V2 model {model_id}.")
if __name__ == "__main__":
main()
- Color guided content (V2 only)
-
# 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 Titan Image Generator G1 V2 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 V2"
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 V2 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 V2 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 V2 model %s", model_id)
return image_bytes
def main():
"""
Entrypoint for Amazon Titan Image Generator V2 example.
"""
try:
logging.basicConfig(level=logging.INFO,
format="%(levelname)s: %(message)s")
model_id = 'amazon.titan-image-generator-v2:0'
# 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 Titan Image Generator V2 model {model_id}.")
if __name__ == "__main__":
main()
- Background removal (V2 only)
-
# 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 Titan Image Generator G1 V2 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 V2"
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 V2 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 V2 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 V2 model %s", model_id)
return image_bytes
def main():
"""
Entrypoint for Amazon Titan Image Generator V2 example.
"""
try:
logging.basicConfig(level=logging.INFO,
format="%(levelname)s: %(message)s")
model_id = 'amazon.titan-image-generator-v2:0'
# 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 Titan Image Generator V2 model {model_id}.")
if __name__ == "__main__":
main()
