Update app.py

app.py

@@ -1,29 +1,27 @@
 import gradio as gr
 from core_pipeline import extract_frames, detect_trees, plot_detections
-import tempfile
 import numpy as np
-import cv2
 
-def process_video(video):
-    with tempfile.NamedTemporaryFile(delete=False, suffix=".mp4") as tmp:
-        tmp.write(video.read())
-        video_path = tmp.name
+def process_video(video_path):
+    if not video_path:
+        return None
 
     frames = extract_frames(video_path)
     results = []
 
-    for i, frame in enumerate(frames):
+    for i, frame in enumerate(frames[:3]):  # limit to 3 sample frames for preview
         detected, bboxes, confs, labels = detect_trees(frame)
         annotated = plot_detections(detected, bboxes)
         results.append(annotated)
 
-    # Stack a preview grid
-    preview = np.hstack(results[:3]) if results else None
-    return preview
+    if results:
+        preview = np.hstack(results)
+        return preview
+    return None
 
 gr.Interface(
     fn=process_video,
-    inputs=gr.Video(label="Upload Drone Video"),
+    inputs=gr.Video(label="Upload Drone Video", type="filepath"),
     outputs=gr.Image(label="Tree Detections (Sample Frames)"),
     title="🌳 Tree Height Detection from Drone Video",
     description="Upload top-down drone video to detect trees and visualize sample frames. Height estimation is possible if SfM data is provided."