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Runtime error
File size: 4,887 Bytes
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import streamlit as st
import os
import requests
from PIL import Image
from io import BytesIO
# Set up environment variables for API keys
os.environ['CLIPDROP_API_KEY'] = '1143a102dbe21628248d4bb992b391a49dc058c584181ea72e17c2ccd49be9ca69ccf4a2b97fc82c89ff1029578abbea'
os.environ['STABILITY_API_KEY'] = 'sk-GBmsWR78MmCSAWGkkC1CFgWgE6GPgV00pNLJlxlyZWyT3QQO'
os.environ['REPLICATE_API_TOKEN'] = 'Image Upscaling
Upload an image or enter a text prompt to generate and upscale an image.
Choose an image...
Drag and drop file here
Limit 200MB per file • PNG, JPG, JPEG
upscaled_image (1).png
26.3MB
Enter a text prompt:
Perfect soft gradient, osx wallpaper, Faint gradient color, pattern, full screen, colorful, uhd, 8k --ar 16:9
109/1000
Uploaded image successfully!
ReplicateError: Incorrect authentication token. Learn how to authenticate and get your API token here: https://replicate.com/docs/reference/http#authentication
Traceback:
File "/home/user/.local/lib/python3.10/site-packages/streamlit/runtime/scriptrunner/script_runner.py", line 565, in _run_script
exec(code, module.__dict__)
File "/home/user/app/app.py", line 91, in <module>
main()
File "/home/user/app/app.py", line 80, in main
img = upscale_image("temp_img.png")
File "/home/user/app/app.py", line 20, in upscale_image
output = replicate.run(
File "/home/user/.local/lib/python3.10/site-packages/replicate/client.py", line 127, in run
version = model.versions.get(m.group("version"))
File "/home/user/.local/lib/python3.10/site-packages/replicate/version.py", line 62, in get
resp = self._client._request(
File "/home/user/.local/lib/python3.10/site-packages/replicate/client.py", line 79, in _request
raise ReplicateError(resp.json()["detail"])'
# Importing Replicate and Stability SDK libraries
import replicate
import stability_sdk.interfaces.gooseai.generation.generation_pb2 as generation
def upscale_image(image_path):
# Open the image file
with open(image_path, "rb") as img_file:
# Run the GFPGAN model
output = replicate.run(
"tencentarc/gfpgan:9283608cc6b7be6b65a8e44983db012355fde4132009bf99d976b2f0896856a3",
input={"img": img_file, "version": "v1.4", "scale": 16}
)
# The output is a URI of the processed image
# We will retrieve the image data and save it
response = requests.get(output)
img = Image.open(BytesIO(response.content))
return img
def generate_and_upscale_image(prompt):
# Make a POST request to the ClipDrop text-to-image API
url = 'https://clipdrop-api.co/text-to-image/v1'
headers = {'x-api-key': os.environ['CLIPDROP_API_KEY']}
data = {'prompt': prompt}
response = requests.post(url, headers=headers, data=data)
if response.status_code == 200:
# Get the generated image from the response
img = Image.open(BytesIO(response.content))
# Upscale the generated image using the Stability API
upscale_api = replicate.StabilityInference(
key=os.environ['STABILITY_API_KEY'],
upscale_engine="stable-diffusion-x4-latent-upscaler"
)
upscale_responses = upscale_api.upscale(init_image=img)
if upscale_responses:
# Get the upscaled image from the response
upscaled_img = None
for resp in upscale_responses:
for artifact in resp.artifacts:
if artifact.type == generation.ARTIFACT_IMAGE:
upscaled_img = Image.open(BytesIO(artifact.binary))
break
if upscaled_img:
break
return upscaled_img
else:
st.error('Failed to upscale the image.')
else:
st.error('Failed to generate image from text prompt.')
def main():
st.title("Image Upscaling")
st.write("Upload an image or enter a text prompt to generate and upscale an image.")
uploaded_file = st.file_uploader("Choose an image...", type=["png", "jpg", "jpeg"])
text_prompt = st.text_input("Enter a text prompt:", max_chars=1000)
if uploaded_file is not None:
with open("temp_img.png", "wb") as f:
f.write(uploaded_file.getbuffer())
st.success("Uploaded image successfully!")
if st.button("Upscale Image"):
# Upscale the uploaded image using GFPGAN
img = upscale_image("temp_img.png")
st.image(img, caption='Upscaled Image (GFPGAN)', use_column_width=True)
elif text_prompt != "":
if st.button("Generate and Upscale"):
# Generate and upscale an image from the text prompt
img = generate_and_upscale_image(text_prompt)
if img:
st.image(img, caption='Generated and Upscaled Image', use_column_width=True)
if __name__ == "__main__":
main()
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