| from __future__ import annotations | |
| from typing import Optional, Dict, Tuple | |
| from PIL import Image | |
| import numpy as np | |
| import cv2 | |
| import os | |
| def pil_from_path(path: str) -> Optional[Image.Image]: | |
| try: | |
| return Image.open(path).convert("RGB") | |
| except Exception: | |
| return None | |
| def first_frame(path: str, max_side: int = 960) -> Tuple[Optional[Image.Image], Dict[str, float]]: | |
| info: Dict[str, float] = {} | |
| try: | |
| cap = cv2.VideoCapture(path) | |
| if not cap.isOpened(): | |
| return None, {"error": "Cannot open video"} | |
| fps = cap.get(cv2.CAP_PROP_FPS) or 0.0 | |
| w = int(cap.get(cv2.CAP_PROP_FRAME_WIDTH) or 0) | |
| h = int(cap.get(cv2.CAP_PROP_FRAME_HEIGHT) or 0) | |
| frames = int(cap.get(cv2.CAP_PROP_FRAME_COUNT) or 0) | |
| ok, frame = cap.read() | |
| cap.release() | |
| if not ok or frame is None: | |
| return None, {"error": "Failed to read first frame"} | |
| frame = cv2.cvtColor(frame, cv2.COLOR_BGR2RGB) | |
| scale = min(1.0, max_side / max(h, w)) if max(h, w) > 0 else 1.0 | |
| if scale < 1.0: | |
| frame = cv2.resize(frame, (int(w*scale), int(h*scale)), interpolation=cv2.INTER_AREA) | |
| dur = (frames / fps) if fps > 0 else 0.0 | |
| return Image.fromarray(frame), {"width": w, "height": h, "fps": round(fps,3), "frames": frames, "duration_s": round(dur,2)} | |
| except Exception as e: | |
| return None, {"error": str(e)} | |
| def mask_debug_on_image(img: Image.Image) -> Image.Image: | |
| """Classical single-frame mask heuristic for quick sanity checks (no models).""" | |
| ar = np.array(img) | |
| if ar.ndim == 3 and ar.shape[2] == 3: | |
| gray = cv2.cvtColor(ar, cv2.COLOR_RGB2GRAY) | |
| else: | |
| gray = ar if ar.ndim == 2 else cv2.cvtColor(ar, cv2.COLOR_RGBA2GRAY) | |
| edges = cv2.Canny(gray, 80, 160) | |
| edges = cv2.dilate(edges, cv2.getStructuringElement(cv2.MORPH_ELLIPSE, (3, 3)), 1) | |
| border = np.concatenate([gray[0, :], gray[-1, :], gray[:, 0], gray[:, -1]]) | |
| bg_median = np.median(border) | |
| diff = np.abs(gray.astype(np.float32) - bg_median) | |
| thresh = (diff > 28).astype(np.uint8) * 255 | |
| mask = cv2.bitwise_or(thresh, edges) | |
| k7 = cv2.getStructuringElement(cv2.MORPH_ELLIPSE, (7, 7)) | |
| mask = cv2.morphologyEx(mask, cv2.MORPH_CLOSE, k7) | |
| mask = cv2.morphologyEx(mask, cv2.MORPH_OPEN, k7) | |
| mask_c = cv2.cvtColor(mask, cv2.COLOR_GRAY2RGB) | |
| overlay = (0.6 * ar + 0.4 * np.dstack([mask, np.zeros_like(mask), np.zeros_like(mask)])).astype(np.uint8) | |
| return Image.fromarray(overlay) | |