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app.py

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+import gradio as gr
+import cv2
+import numpy as np
+from pathlib import Path
+
+# Import the existing homography and warping function from your existing script
+from billboard import apply_homography_and_warp
+
+
+# Define a function to select points on the image (similar to your `get_point_interface`)
+def get_point_interface(original_frame, points, evt: gr.SelectData):
+    x, y = evt.index
+    if points is None:
+        points = []
+    points = points.copy()  # Make a copy to avoid modifying in-place
+    points.append((x, y))
+
+    # Draw the points and lines on the image
+    image = original_frame.copy()
+    for pt in points:
+        cv2.circle(image, pt, 5, (255, 0, 0), -1)
+    if len(points) > 1:
+        for i in range(len(points) - 1):
+            cv2.line(image, points[i], points[i + 1], (255, 0, 0), 2)
+
+    return image, points
+
+
+# Function to process and apply homography (this will call your existing function)
+def process_images(source_image, dest_image, roi_points):
+    # Ensure that exactly four points are selected
+    if len(roi_points) != 4:
+        return "Error: Please select exactly four points."
+
+    # Convert images to correct format (if not already in uint8)
+    img_src = np.array(source_image)
+    img_dst = np.array(dest_image)
+
+    # Apply homography and get the warped image
+    result_img = apply_homography_and_warp(img_src, img_dst, np.array(roi_points))
+
+    # Return the processed image
+    return result_img
+
+
+# Gradio interface setup
+with gr.Blocks(title="Homography Warping App") as demo:
+    gr.Markdown("# Homography Warping App")
+    gr.Markdown(
+        "Upload two images (source and destination), select the four points for ROI on the destination image, and click 'Process Images' to warp the source image onto the destination."
+    )
+
+    with gr.Row(equal_height=True):
+        source_image_input = gr.Image(label="Upload Source Image")
+        dest_image_input = gr.Image(label="Upload Destination Image")
+
+    with gr.Column():
+        dest_image_roi = gr.Image(label="Click to select ROI points on destination image")
+        original_frame_state = gr.State(None)
+        selected_points = gr.State([])
+        clear_points_button = gr.Button("Clear Points")
+        process_button = gr.Button("Process Images")
+
+    with gr.Row():
+        output_image = gr.Image(label="Wrapped Image")
+
+    examples = [
+        ["./images/Apollo-8-Launch.png", "./images/times_square.jpg"],
+    ]
+
+    with gr.Row():
+        gr.Examples(
+            examples=examples,
+            inputs=[source_image_input, dest_image_roi],
+            label="Load Example Images",
+        )
+
+    dest_image_input.upload(
+        lambda img: img, inputs=dest_image_input, outputs=dest_image_roi  # Simply return the uploaded image
+    )
+
+    # Adding the ROI point selection functionality
+    dest_image_roi.select(
+        get_point_interface, inputs=[dest_image_roi, selected_points], outputs=[dest_image_roi, selected_points]
+    )
+
+    # Clear the selected points
+    clear_points_button.click(
+        fn=lambda original_frame: (original_frame, []),
+        inputs=dest_image_input,
+        outputs=[dest_image_roi, selected_points],
+    )
+
+    # Callback for processing the images
+    process_button.click(
+        process_images, inputs=[source_image_input, dest_image_roi, selected_points], outputs=output_image
+    )
+
+
+# Launch the Gradio app
+demo.launch()

requirements.txt

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+opencv-python==4.10.0.84 
+gradio==5.5.0