Refactor imports in ProjectView for clarity and maintainability

croppa/project_view.py

@@ -0,0 +1,110 @@
+from pathlib import Path
+from typing import Dict
+
+import cv2
+import numpy as np
+
+
+class ProjectView:
+    """Project view that displays videos in current directory with progress bars"""
+    
+    THUMBNAIL_SIZE = (200, 150)
+    THUMBNAIL_MARGIN = 20
+    PROGRESS_BAR_HEIGHT = 8
+    TEXT_HEIGHT = 30
+    
+    BG_COLOR = (40, 40, 40)
+    THUMBNAIL_BG_COLOR = (60, 60, 60)
+    PROGRESS_BG_COLOR = (80, 80, 80)
+    PROGRESS_FILL_COLOR = (0, 120, 255)
+    TEXT_COLOR = (255, 255, 255)
+    SELECTED_COLOR = (255, 165, 0)
+    
+    def __init__(self, directory: Path, video_editor):
+        self.directory = directory
+        self.video_editor = video_editor
+        self.video_files = []
+        self.thumbnails: Dict[Path, np.ndarray] = {}
+        self.progress_data = {}
+        self.selected_index = 0
+        self.scroll_offset = 0
+        self.items_per_row = 2
+        self.window_width = 1200
+        self.window_height = 800
+        
+        self._load_video_files()
+        self._load_progress_data()
+    
+    def _calculate_thumbnail_size(self, window_width: int) -> tuple:
+        available_width = window_width - self.THUMBNAIL_MARGIN
+        item_width = (available_width - (self.items_per_row - 1) * self.THUMBNAIL_MARGIN) // self.items_per_row
+        thumbnail_width = max(50, item_width)
+        thumbnail_height = int(thumbnail_width * self.THUMBNAIL_SIZE[1] / self.THUMBNAIL_SIZE[0])
+        return (thumbnail_width, thumbnail_height)
+    
+    def _load_video_files(self):
+        self.video_files = []
+        for file_path in self.directory.iterdir():
+            if (file_path.is_file() and 
+                file_path.suffix.lower() in self.video_editor.VIDEO_EXTENSIONS):
+                self.video_files.append(file_path)
+        self.video_files.sort(key=lambda x: x.name)
+    
+    def _load_progress_data(self):
+        self.progress_data = {}
+        for video_path in self.video_files:
+            state_file = video_path.with_suffix('.json')
+            if state_file.exists():
+                try:
+                    with open(state_file, 'r') as f:
+                        import json
+                        state = json.load(f)
+                    current_frame = state.get('current_frame', 0)
+                    cap = cv2.VideoCapture(str(video_path))
+                    if cap.isOpened():
+                        total_frames = int(cap.get(cv2.CAP_PROP_FRAME_COUNT))
+                        cap.release()
+                        if total_frames > 0:
+                            progress = current_frame / (total_frames - 1)
+                            self.progress_data[video_path] = {
+                                'current_frame': current_frame,
+                                'total_frames': total_frames,
+                                'progress': progress
+                            }
+                except Exception as e:  # noqa: BLE001 - preserve original behavior
+                    print(f"Error loading progress for {video_path.name}: {e}")
+    
+    def refresh_progress_data(self):
+        self._load_progress_data()
+    
+    def get_progress_for_video(self, video_path: Path) -> float:
+        if video_path in self.progress_data:
+            return self.progress_data[video_path]['progress']
+        return 0.0
+    
+    def get_thumbnail_for_video(self, video_path: Path, size: tuple = None) -> np.ndarray:
+        if size is None:
+            size = self.THUMBNAIL_SIZE
+        if video_path in self.thumbnails:
+            original_thumbnail = self.thumbnails[video_path]
+            return cv2.resize(original_thumbnail, size)
+        try:
+            cap = cv2.VideoCapture(str(video_path))
+            if cap.isOpened():
+                total_frames = int(cap.get(cv2.CAP_PROP_FRAME_COUNT))
+                if total_frames > 0:
+                    middle_frame = total_frames // 2
+                    cap.set(cv2.CAP_PROP_POS_FRAMES, middle_frame)
+                    ret, frame = cap.read()
+                    if ret:
+                        original_thumbnail = cv2.resize(frame, self.THUMBNAIL_SIZE)
+                        self.thumbnails[video_path] = original_thumbnail
+                        cap.release()
+                        return cv2.resize(original_thumbnail, size)
+            cap.release()
+        except Exception as e:  # noqa: BLE001 - preserve original behavior
+            print(f"Error generating thumbnail for {video_path.name}: {e}")
+        placeholder = np.full((size[1], size[0], 3), self.THUMBNAIL_BG_COLOR, dtype=np.uint8)
+        return placeholder
+    
+    # draw() and input handling remain in main editor for now to minimize churn