Update main.py

main.py

@@ -1,41 +1,82 @@
 import streamlit as st
-import replicate
-import os
 import requests
 from PIL import Image
 from io import BytesIO
+import getpass, os
+import warnings
+from stability_sdk import client
+import stability_sdk.interfaces.gooseai.generation.generation_pb2 as generation
+import replicate
+
+# API keys
+api_key = '1143a102dbe21628248d4bb992b391a49dc058c584181ea72e17c2ccd49be9ca69ccf4a2b97fc82c89ff1029578abbea'
+os.environ['STABILITY_KEY'] = 'sk-GBmsWR78MmCSAWGkkC1CFgWgE6GPgV00pNLJlxlyZWyT3QQO'
+os.environ['REPLICATE_API_TOKEN'] = 'r8_0a77UG8yfrNXOS6xHhUTLh80dJQ5kxO0CTLmq'  # Replace with your actual API token
+
+# Increase the pixel limit
+Image.MAX_IMAGE_PIXELS = None
+
+# Establish connection to Stability API
+stability_api = client.StabilityInference(
+    key=os.environ['STABILITY_KEY'], 
+    upscale_engine="esrgan-v1-x2plus",
+    verbose=True,
+)
+
+# ClipDrop API function
+def generate_image(prompt):
+    headers = {'x-api-key': api_key}
+    body_params = {'prompt': (None, prompt, 'text/plain')}
+    response = requests.post('https://clipdrop-api.co/text-to-image/v1', files=body_params, headers=headers)
+
+    if response.status_code == 200:
+        return Image.open(BytesIO(response.content))
+    else:
+        st.write(f"Request failed with status code {response.status_code}")
+        return None
 
-# Set up environment variable for Replicate API Token
-os.environ['REPLICATE_API_TOKEN'] = 'r8_3V5WKOBwbbuL0DQGMliP0972IAVIBo62Lmi8I'  # Replace with your actual API token
+# Stability API function
+def upscale_image_stability(img):
+    answers = stability_api.upscale(init_image=img)
 
-def upscale_image(image_path):
-    # Open the image file
+    for resp in answers:
+        for artifact in resp.artifacts:
+            if artifact.finish_reason == generation.FILTER:
+                warnings.warn(
+                    "Your request activated the API's safety filters and could not be processed."
+                    "Please submit a different image and try again.")
+            if artifact.type == generation.ARTIFACT_IMAGE:
+                return Image.open(io.BytesIO(artifact.binary))
+
+# GFPGAN function
+def upscale_image_gfpgan(image_path):
     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))
-        img.save("upscaled.png")  # Save the upscaled image
-        return img
-
-def main():
-    st.title("Image Upscaling")
-    st.write("Upload an image and it will be upscaled.")
-
-    uploaded_file = st.file_uploader("Choose an image...", type="png")
-    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"):
-            img = upscale_image("temp_img.png")
-            st.image(img, caption='Upscaled Image', use_column_width=True)
-
-if __name__ == "__main__":
-    main()
+        return Image.open(BytesIO(response.content))
+
+# Streamlit UI
+st.title("Image Generator and Upscaler")
+
+prompt = st.text_input("Enter a prompt for the image generation")
+
+if st.button("Generate and Upscale"):
+    if prompt:
+        img1 = generate_image(prompt)
+
+        if img1:
+            st.image(img1, caption="Generated Image", use_column_width=True)
+            img1.save('generated_image.png')
+
+            img2 = upscale_image_stability(img1)
+            st.image(img2, caption="Upscaled Image (Stability API)", use_column_width=True)
+            img2.save('upscaled_image_stability.png')
+
+            img3 = upscale_image_gfpgan('upscaled_image_stability.png')
+            st.image(img3, caption="Upscaled Image (GFPGAN)", use_column_width=True)
+            img3.save('upscaled_image_gfpgan.png')
+    else:
+        st.write("Please enter a prompt")