Create app.py

app.py

@@ -0,0 +1,92 @@
+import cv2
+import numpy as np
+import gradio as gr
+import tempfile
+import os
+from tqdm import tqdm
+
+# ----------------------------
+# LOAD MODEL (GLOBAL)
+# ----------------------------
+MODEL_PATH = "mosaic.t7"  # place model in repo root
+net = cv2.dnn.readNetFromTorch(MODEL_PATH)
+
+
+def style_video(input_video):
+    # ----------------------------
+    # OPEN INPUT VIDEO
+    # ----------------------------
+    cap = cv2.VideoCapture(input_video)
+    if not cap.isOpened():
+        raise RuntimeError("Could not open video")
+
+    fps = cap.get(cv2.CAP_PROP_FPS)
+    width = int(cap.get(cv2.CAP_PROP_FRAME_WIDTH))
+    height = int(cap.get(cv2.CAP_PROP_FRAME_HEIGHT))
+    total_frames = int(cap.get(cv2.CAP_PROP_FRAME_COUNT))
+
+    # ----------------------------
+    # TEMP OUTPUT FILE
+    # ----------------------------
+    temp_out = tempfile.NamedTemporaryFile(delete=False, suffix=".mp4")
+    temp_out.close()
+
+    fourcc = cv2.VideoWriter_fourcc(*"mp4v")
+    writer = cv2.VideoWriter(
+        temp_out.name,
+        fourcc,
+        fps,
+        (width, height)
+    )
+
+    # ----------------------------
+    # PROCESS FRAMES
+    # ----------------------------
+    for _ in tqdm(range(total_frames), desc="Styling frames"):
+        ret, frame = cap.read()
+        if not ret:
+            break
+
+        blob = cv2.dnn.blobFromImage(
+            frame,
+            1.0,
+            (width, height),
+            (103.939, 116.779, 123.680),
+            swapRB=False,
+            crop=False
+        )
+
+        net.setInput(blob)
+        output = net.forward()
+
+        output = output.reshape(3, output.shape[2], output.shape[3])
+        output[0] += 103.939
+        output[1] += 116.779
+        output[2] += 123.680
+        output = output.transpose(1, 2, 0)
+
+        output = np.clip(output, 0, 255).astype("uint8")
+        writer.write(output)
+
+    # ----------------------------
+    # CLEANUP
+    # ----------------------------
+    cap.release()
+    writer.release()
+
+    return temp_out.name
+
+
+# ----------------------------
+# GRADIO UI
+# ----------------------------
+app = gr.Interface(
+    fn=style_video,
+    inputs=gr.Video(label="Upload Video"),
+    outputs=gr.Video(label="Styled Video"),
+    title="Neural Style Transfer on Video",
+    description="Applies fast neural style transfer (Torch .t7) frame-by-frame using OpenCV."
+)
+
+if __name__ == "__main__":
+    app.launch()