Create app.py

app.py

@@ -0,0 +1,30 @@
+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
+
+    frames = extract_frames(video_path)
+    results = []
+
+    for i, frame in enumerate(frames):
+        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
+
+gr.Interface(
+    fn=process_video,
+    inputs=gr.Video(label="Upload Drone Video"),
+    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."
+).launch()