111 lines
4.5 KiB
Python
111 lines
4.5 KiB
Python
from pathlib import Path
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from typing import Dict
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import cv2
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import numpy as np
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class ProjectView:
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"""Project view that displays videos in current directory with progress bars"""
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THUMBNAIL_SIZE = (200, 150)
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THUMBNAIL_MARGIN = 20
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PROGRESS_BAR_HEIGHT = 8
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TEXT_HEIGHT = 30
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BG_COLOR = (40, 40, 40)
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THUMBNAIL_BG_COLOR = (60, 60, 60)
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PROGRESS_BG_COLOR = (80, 80, 80)
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PROGRESS_FILL_COLOR = (0, 120, 255)
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TEXT_COLOR = (255, 255, 255)
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SELECTED_COLOR = (255, 165, 0)
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def __init__(self, directory: Path, video_editor):
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self.directory = directory
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self.video_editor = video_editor
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self.video_files = []
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self.thumbnails: Dict[Path, np.ndarray] = {}
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self.progress_data = {}
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self.selected_index = 0
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self.scroll_offset = 0
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self.items_per_row = 2
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self.window_width = 1200
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self.window_height = 800
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self._load_video_files()
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self._load_progress_data()
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def _calculate_thumbnail_size(self, window_width: int) -> tuple:
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available_width = window_width - self.THUMBNAIL_MARGIN
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item_width = (available_width - (self.items_per_row - 1) * self.THUMBNAIL_MARGIN) // self.items_per_row
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thumbnail_width = max(50, item_width)
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thumbnail_height = int(thumbnail_width * self.THUMBNAIL_SIZE[1] / self.THUMBNAIL_SIZE[0])
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return (thumbnail_width, thumbnail_height)
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def _load_video_files(self):
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self.video_files = []
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for file_path in self.directory.iterdir():
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if (file_path.is_file() and
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file_path.suffix.lower() in self.video_editor.VIDEO_EXTENSIONS):
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self.video_files.append(file_path)
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self.video_files.sort(key=lambda x: x.name)
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def _load_progress_data(self):
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self.progress_data = {}
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for video_path in self.video_files:
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state_file = video_path.with_suffix('.json')
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if state_file.exists():
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try:
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with open(state_file, 'r') as f:
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import json
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state = json.load(f)
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current_frame = state.get('current_frame', 0)
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cap = cv2.VideoCapture(str(video_path))
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if cap.isOpened():
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total_frames = int(cap.get(cv2.CAP_PROP_FRAME_COUNT))
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cap.release()
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if total_frames > 0:
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progress = current_frame / (total_frames - 1)
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self.progress_data[video_path] = {
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'current_frame': current_frame,
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'total_frames': total_frames,
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'progress': progress
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}
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except Exception as e: # noqa: BLE001 - preserve original behavior
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print(f"Error loading progress for {video_path.name}: {e}")
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def refresh_progress_data(self):
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self._load_progress_data()
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def get_progress_for_video(self, video_path: Path) -> float:
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if video_path in self.progress_data:
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return self.progress_data[video_path]['progress']
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return 0.0
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def get_thumbnail_for_video(self, video_path: Path, size: tuple = None) -> np.ndarray:
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if size is None:
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size = self.THUMBNAIL_SIZE
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if video_path in self.thumbnails:
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original_thumbnail = self.thumbnails[video_path]
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return cv2.resize(original_thumbnail, size)
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try:
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cap = cv2.VideoCapture(str(video_path))
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if cap.isOpened():
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total_frames = int(cap.get(cv2.CAP_PROP_FRAME_COUNT))
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if total_frames > 0:
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middle_frame = total_frames // 2
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cap.set(cv2.CAP_PROP_POS_FRAMES, middle_frame)
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ret, frame = cap.read()
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if ret:
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original_thumbnail = cv2.resize(frame, self.THUMBNAIL_SIZE)
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self.thumbnails[video_path] = original_thumbnail
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cap.release()
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return cv2.resize(original_thumbnail, size)
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cap.release()
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except Exception as e: # noqa: BLE001 - preserve original behavior
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print(f"Error generating thumbnail for {video_path.name}: {e}")
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placeholder = np.full((size[1], size[0], 3), self.THUMBNAIL_BG_COLOR, dtype=np.uint8)
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return placeholder
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# draw() and input handling remain in main editor for now to minimize churn
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