app.py

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()