Create app.py

app.py

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+import cv2
+import numpy as np
+
+import gradio as gr
+import os
+import shutil
+import spaces
+
+class PanoramaGenerator:
+    def __init__(self, video_path):
+        self.video_path = video_path
+        self.frames = []
+
+    def extract_frames(self, frame_interval=10):
+        cap = cv2.VideoCapture(self.video_path)
+
+        if not cap.isOpened():
+            raise ValueError("Error opening video file")
+
+        frame_count = 0
+        while True:
+            ret, frame = cap.read()
+
+            if not ret:
+                break
+
+            # Extract frame
+            if frame_count % frame_interval == 0:
+                # Resize frame
+                resized_frame = cv2.resize(frame, (0, 0), fx=0.5, fy=0.5)
+                self.frames.append(resized_frame)
+
+            frame_count += 1
+
+        cap.release()
+        return self.frames
+
+    def create_panorama(self):
+        if len(self.frames) < 2:
+            raise ValueError("Not enough frames to create panorama")
+
+        stitcher = cv2.Stitcher_create(mode=cv2.Stitcher_PANORAMA)
+
+        # Attempt to stitch frames
+        status, panorama = stitcher.stitch(self.frames)
+
+        # Check if stitching was successful
+        if status != cv2.Stitcher_OK:
+            raise RuntimeError(f"Stitching failed with error code {status}")
+
+        return panorama
+
+    def save_panorama(self, output_path="panorama.jpg"):
+        panorama = self.create_panorama()
+        cv2.imwrite(output_path, panorama)
+        return output_path
+
+
+
+
+def process_video(video_file):
+    # Save the uploaded video to a temporary file
+    temp_video_path = "temp_video.mp4"
+    shutil.copy(video_file.name, temp_video_path)
+
+    # Generate the panorama
+    panorama_gen = PanoramaGenerator(temp_video_path)
+    panorama_gen.extract_frames()
+    panorama_path = panorama_gen.save_panorama()
+
+    # Clean up the temporary video file
+    os.remove(temp_video_path)
+
+    return panorama_path
+
+@spaces.GPU
+def generate_and_display(video_file):
+    panorama_path = process_video(video_file)
+    return panorama_path, panorama_path
+
+with gr.Blocks() as demo:
+    gr.Markdown("# Video to Panorama Generator")
+
+    with gr.Row():
+        with gr.Column():
+            video_input = gr.File(label="Upload Video", file_types=["video"])
+            generate_button = gr.Button("Generate Panorama")
+        with gr.Column():
+            panorama_output = gr.Image(label="Generated Panorama")
+            download_button = gr.DownloadButton("Download Panorama", file_name="panorama.jpg")
+
+    generate_button.click(
+        fn=generate_and_display,
+        inputs=video_input,
+        outputs=[panorama_output, download_button]
+    )
+
+demo.launch()