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app.py

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+import gradio as gr
+import cv2
+from tqdm import tqdm
+import os
+import tempfile
+
+
+def resize(movie, x, y, original_x, original_y, progress=gr.Progress(track_tqdm=True)):
+   mp4_path = os.path.splitext(os.path.basename(movie))[0]
+   cap = cv2.VideoCapture(movie)
+   width, height = cap.get(cv2.CAP_PROP_FRAME_WIDTH), cap.get(cv2.CAP_PROP_FRAME_HEIGHT)  # 動画のサイズを取得
+
+   if original_x == 0:
+      original_x = width
+      original_y = height
+   # リサイズを動画のサイズに合わせる
+   target_w = round(width / (original_x / x))
+   target_h = round(height / (original_y / y))
+   fps = cap.get(cv2.CAP_PROP_FPS)
+   fourcc = cv2.VideoWriter_fourcc('m', 'p', '4', 'v')
+   with tempfile.NamedTemporaryFile(suffix=".h5", delete=False) as temp_file:
+      temp_file_path = f"{mp4_path}_{x}_{y}_resize.mp4"
+      writer = cv2.VideoWriter(temp_file_path, fourcc, fps, (target_w, target_h))
+      for i in tqdm(range(int(cap.get(cv2.CAP_PROP_FRAME_COUNT)))):
+         ret, frame = cap.read()
+         if not ret:
+            break
+         frame = cv2.resize(frame, (target_w, target_h))
+         writer.write(frame)
+   return temp_file_path
+
+
+# Create the Gradio interface
+iface = gr.Interface(
+    fn=resize,
+    inputs=[
+        gr.Video(type="mp4", label="Input movie"),
+        gr.inputs.Slider(minimum=0, maximum=3840, step=10, default=1920, label="X"),
+        gr.inputs.Slider(minimum=0, maximum=2160, step=10, default=1080, label="Y"),
+        gr.inputs.Number(default=0, label="Xの元の解像度"),
+        gr.inputs.Number(default=0, label="Yの元の解像度")
+    ],
+    outputs=gr.Video(label="Result"),
+    title="mp4_resize",
+    description="動画をリサイズします"
+)
+
+if __name__ == "__main__":
+   iface.queue().launch()

requirements.txt

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+opencv-python
+tqdm