test

app.py

@@ -35,6 +35,7 @@ iface = gr.Interface(
     title="Image Processor",
     description="Upload an image and download a folder with processed images.",
     flagging_mode="auto",  # Disable the flag button
+    theme="huggingface",
 )
 
 # Launch the app

tmp.txt

@@ -0,0 +1,96 @@
+Create a readme for the following code:
+
+app.py
+
+import gradio as gr
+import os
+import shutil
+
+
+def process_image(input_image):
+    # Step 1: Create or clear the 'images' folder
+    images_folder = "images"
+    if os.path.exists(images_folder):
+        shutil.rmtree(images_folder)  # Remove the folder if it exists
+    os.makedirs(images_folder)  # Create a new 'images' folder
+
+    # Step 2: Save the input image into the 'images' folder
+    input_image_path = os.path.join(images_folder, "input_image.png")
+    input_image.save(input_image_path)
+
+    # # Step 3: Perform some actions (placeholder)
+    os.system("python run_google_lens.py")
+    os.system("python run_clean_images.py")
+
+    # Step 4: Zip the 'images' folder
+    zip_filename = "images.zip"
+    shutil.make_archive("images", "zip", images_folder)
+    shutil.rmtree(images_folder)
+
+    # Step 5: Return the path to the ZIP file
+    return zip_filename
+
+
+# Set up the Gradio interface using Interface instead of Blocks
+iface = gr.Interface(
+    fn=process_image,
+    inputs=gr.Image(type="pil", label="Upload an Image"),
+    outputs=gr.File(label="Download Images Folder"),
+    title="Image Processor",
+    description="Upload an image and download a folder with processed images.",
+    allow_flagging="auto",  # Disable the flag button
+)
+
+# Launch the app
+iface.launch()
+
+---
+
+run_clean_images.py
+
+import os
+import logging
+from cleanvision.imagelab import Imagelab
+
+# Set up logging
+logging.basicConfig(
+    level=logging.INFO,
+    format="%(asctime)s - %(levelname)s - %(message)s",
+)
+
+
+def delete_images_with_issues(directory):
+    # Initialize Imagelab with the directory of images
+    imagelab = Imagelab(directory)
+
+    # Run the inspection to identify images with issues
+    issues = imagelab.find_issues()
+    issue_columns = imagelab.issues.filter(like="issue")
+
+    # Use where to replace rows that don't have any True value with NaN
+    filtered_df = imagelab.issues.where(issue_columns.any(axis=1))
+
+    # Drop the rows with NaN values (i.e., rows where no issue column was True)
+    filtered_df = filtered_df.dropna()
+
+    # Display the filtered DataFrame
+    filtered_df.index.to_list()
+
+    # Iterate over the issues and delete the corresponding images
+    for issue in filtered_df.index.to_list():
+        image_path = issue
+        try:
+            os.remove(image_path)
+            logging.info(f"Deleted: {image_path}")
+        except Exception as e:
+            logging.error(f"Error deleting {image_path}: {e}")
+
+
+if __name__ == "__main__":
+    # path = "/Users/andrewmayes/Project/document-type-detection/data/non_object"
+    path = "/home/user/app/images/"
+
+    delete_images_with_issues(path)
+
+---
+