feat: add timeline overlay and video segment options

- Add --timeline flag to overlay frame numbers as ruler at bottom
- Add --start and --end parameters to process video segments
- Timeline shows evenly-spaced frame numbers with tick marks
- Timeline always horizontal from left to right at bottom
- Segment processing maintains actual frame numbers in timeline
- Update all extraction and analysis functions to support segments

main.py

@@ -13,6 +13,7 @@ import numpy as np
 import matplotlib.pyplot as plt
 from pathlib import Path
 import uuid
+import math
 
 
 def calculate_line_difference(line1, line2):
@@ -69,7 +70,7 @@ def generate_change_graph(changes, output_path, threshold=None):
     print(f"Change graph saved to: {output_path}")
 
 
-def analyze_changes_only(video_path, x_column=None, y_row=None, debug_output=None):
+def analyze_changes_only(video_path, x_column=None, y_row=None, debug_output=None, start_frame=0, end_frame=None):
     """
     Analyze changes in video without generating strip image.
     Used for debug mode to generate change threshold graphs.
@@ -79,6 +80,8 @@ def analyze_changes_only(video_path, x_column=None, y_row=None, debug_output=Non
         x_column: X-coordinate of column to analyze (if column mode)
         y_row: Y-coordinate of row to analyze (if row mode)
         debug_output: Base path for debug outputs
+        start_frame: First frame to process (0-based)
+        end_frame: Last frame to process (None = until end)
         
     Returns:
         List of change values
@@ -102,7 +105,11 @@ def analyze_changes_only(video_path, x_column=None, y_row=None, debug_output=Non
             raise ValueError(f"Row {y_row} is outside video height ({frame_height})")
         print(f"Analyzing row {y_row} from {frame_width}x{frame_height} frames")
     
-    print(f"Processing {total_frames} frames for change analysis...")
+    # Set end frame if not specified
+    if end_frame is None:
+        end_frame = total_frames - 1
+    
+    print(f"Processing frames {start_frame} to {end_frame} ({end_frame - start_frame + 1} frames) for change analysis...")
     
     changes = []
     previous_line = None
@@ -112,6 +119,15 @@ def analyze_changes_only(video_path, x_column=None, y_row=None, debug_output=Non
         ret, frame = cap.read()
         if not ret:
             break
+        
+        # Skip frames before start
+        if frame_idx < start_frame:
+            frame_idx += 1
+            continue
+        
+        # Stop after end frame
+        if frame_idx > end_frame:
+            break
             
         # Extract current line (column or row)
         if x_column is not None:
@@ -127,8 +143,8 @@ def analyze_changes_only(video_path, x_column=None, y_row=None, debug_output=Non
         previous_line = current_line
         frame_idx += 1
         
-        if frame_idx % 100 == 0:
+        if (frame_idx - start_frame) % 100 == 0:
-            print(f"Analyzed {frame_idx}/{total_frames} frames")
+            print(f"Analyzed {frame_idx - start_frame}/{end_frame - start_frame + 1} frames")
     
     cap.release()
     
@@ -167,7 +183,51 @@ def analyze_changes_only(video_path, x_column=None, y_row=None, debug_output=Non
     return changes
 
 
-def extract_column_strip(video_path, x_column, output_path, change_threshold=0.005, relax=0):
+def add_timeline_overlay(image, frame_numbers):
+    """
+    Add frame number overlay as a timeline/ruler at the top of the image.
+    Always horizontal from left to right.
+    
+    Args:
+        image: The strip image to add overlay to
+        frame_numbers: List of frame numbers that were included
+    
+    Returns:
+        Image with timeline overlay
+    """
+    if not frame_numbers:
+        return image
+    
+    overlay = image.copy()
+    font = cv2.FONT_HERSHEY_SIMPLEX
+    font_scale = 0.4
+    font_thickness = 1
+    text_color = (255, 255, 0)  # Cyan for visibility
+    
+    # Calculate text size for spacing
+    (text_width, text_height), _ = cv2.getTextSize("00000", font, font_scale, font_thickness)
+    
+    # Horizontal timeline at the top from left to right
+    # Calculate spacing to avoid overlap
+    available_width = image.shape[1]
+    num_labels = min(len(frame_numbers), max(10, available_width // (text_width + 10)))
+    step = max(1, len(frame_numbers) // num_labels)
+    
+    for i in range(0, len(frame_numbers), step):
+        frame_num = frame_numbers[i]
+        text = str(frame_num)
+        x_pos = int((i / len(frame_numbers)) * available_width)
+        
+        # Add small tick mark
+        cv2.line(overlay, (x_pos, 0), (x_pos, 10), text_color, 1)
+        # Add text
+        cv2.putText(overlay, text, (x_pos + 2, text_height + 12),
+                   font, font_scale, text_color, font_thickness, cv2.LINE_AA)
+    
+    return overlay
+
+
+def extract_column_strip(video_path, x_column, output_path, change_threshold=0.005, relax=0, timeline=False, start_frame=0, end_frame=None):
     """
     Extract vertical strip at x_column from each frame of the video.
     Only include frames where the change exceeds the threshold.
@@ -178,6 +238,9 @@ def extract_column_strip(video_path, x_column, output_path, change_threshold=0.0
         output_path: Path for output image
         change_threshold: Minimum change threshold (0-1) to include frame
         relax: Number of extra frames to include before/after threshold frames
+        timeline: If True, overlay frame numbers as timeline
+        start_frame: First frame to process (0-based)
+        end_frame: Last frame to process (None = until end)
     """
     cap = cv2.VideoCapture(str(video_path))
     
@@ -192,7 +255,11 @@ def extract_column_strip(video_path, x_column, output_path, change_threshold=0.0
     if x_column >= frame_width:
         raise ValueError(f"Column {x_column} is outside video width ({frame_width})")
     
-    print(f"Processing {total_frames} frames...")
+    # Set end frame if not specified
+    if end_frame is None:
+        end_frame = total_frames - 1
+    
+    print(f"Processing frames {start_frame} to {end_frame} ({end_frame - start_frame + 1} frames)...")
     print(f"Extracting column {x_column} from {frame_width}x{frame_height} frames")
     print(f"Change threshold: {change_threshold}")
     if relax > 0:
@@ -201,6 +268,7 @@ def extract_column_strip(video_path, x_column, output_path, change_threshold=0.0
     # First pass: collect all columns and identify significant frames
     all_columns = []
     changes = []
+    frame_numbers = []
     previous_column = None
     
     frame_idx = 0
@@ -208,10 +276,20 @@ def extract_column_strip(video_path, x_column, output_path, change_threshold=0.0
         ret, frame = cap.read()
         if not ret:
             break
+        
+        # Skip frames before start
+        if frame_idx < start_frame:
+            frame_idx += 1
+            continue
+        
+        # Stop after end frame
+        if frame_idx > end_frame:
+            break
             
         # Extract current column
         current_column = frame[:, x_column, :].copy()
         all_columns.append(current_column)
+        frame_numbers.append(frame_idx)
         
         # Calculate change from previous frame
         if previous_column is not None:
@@ -223,8 +301,8 @@ def extract_column_strip(video_path, x_column, output_path, change_threshold=0.0
         previous_column = current_column
         frame_idx += 1
         
-        if frame_idx % 100 == 0:
+        if (frame_idx - start_frame) % 100 == 0:
-            print(f"Processed {frame_idx}/{total_frames} frames")
+            print(f"Processed {frame_idx - start_frame}/{end_frame - start_frame + 1} frames")
     
     cap.release()
     
@@ -239,8 +317,14 @@ def extract_column_strip(video_path, x_column, output_path, change_threshold=0.0
             for j in range(start, end):
                 include_mask[j] = True
     
-    # Collect significant columns
+    # Collect significant columns with actual frame numbers
-    significant_columns = [col for i, col in enumerate(all_columns) if include_mask[i]]
+    significant_columns = []
+    significant_frame_numbers = []
+    for i, col in enumerate(all_columns):
+        if include_mask[i]:
+            significant_columns.append(col)
+            significant_frame_numbers.append(frame_numbers[i])
+    
     included_frames = sum(include_mask)
     skipped_frames = len(all_columns) - included_frames
     
@@ -250,7 +334,11 @@ def extract_column_strip(video_path, x_column, output_path, change_threshold=0.0
     # Convert list to numpy array
     strip_image = np.stack(significant_columns, axis=1)
     
-    print(f"Original frames: {total_frames}")
+    # Add timeline overlay if requested
+    if timeline:
+        strip_image = add_timeline_overlay(strip_image, significant_frame_numbers)
+    
+    print(f"Original frames in segment: {len(all_columns)}")
     print(f"Included frames: {included_frames}")
     print(f"Skipped frames: {skipped_frames}")
     print(f"Compression ratio: {skipped_frames/total_frames:.1%}")
@@ -261,7 +349,7 @@ def extract_column_strip(video_path, x_column, output_path, change_threshold=0.0
     cv2.imwrite(str(output_path), strip_image)
 
 
-def extract_row_strip(video_path, y_row, output_path, change_threshold=0.01, relax=0):
+def extract_row_strip(video_path, y_row, output_path, change_threshold=0.01, relax=0, timeline=False, start_frame=0, end_frame=None):
     """
     Extract horizontal strip at y_row from each frame of the video.
     Only include frames where the change exceeds the threshold.
@@ -272,6 +360,9 @@ def extract_row_strip(video_path, y_row, output_path, change_threshold=0.01, rel
         output_path: Path for output image
         change_threshold: Minimum change threshold (0-1) to include frame
         relax: Number of extra frames to include before/after threshold frames
+        timeline: If True, overlay frame numbers as timeline
+        start_frame: First frame to process (0-based)
+        end_frame: Last frame to process (None = until end)
     """
     cap = cv2.VideoCapture(str(video_path))
     
@@ -286,7 +377,11 @@ def extract_row_strip(video_path, y_row, output_path, change_threshold=0.01, rel
     if y_row >= frame_height:
         raise ValueError(f"Row {y_row} is outside video height ({frame_height})")
     
-    print(f"Processing {total_frames} frames...")
+    # Set end frame if not specified
+    if end_frame is None:
+        end_frame = total_frames - 1
+    
+    print(f"Processing frames {start_frame} to {end_frame} ({end_frame - start_frame + 1} frames)...")
     print(f"Extracting row {y_row} from {frame_width}x{frame_height} frames")
     print(f"Change threshold: {change_threshold}")
     if relax > 0:
@@ -295,6 +390,7 @@ def extract_row_strip(video_path, y_row, output_path, change_threshold=0.01, rel
     # First pass: collect all rows and identify significant frames
     all_rows = []
     changes = []
+    frame_numbers = []
     previous_row = None
     
     frame_idx = 0
@@ -302,10 +398,20 @@ def extract_row_strip(video_path, y_row, output_path, change_threshold=0.01, rel
         ret, frame = cap.read()
         if not ret:
             break
+        
+        # Skip frames before start
+        if frame_idx < start_frame:
+            frame_idx += 1
+            continue
+        
+        # Stop after end frame
+        if frame_idx > end_frame:
+            break
             
         # Extract current row
         current_row = frame[y_row, :, :].copy()
         all_rows.append(current_row)
+        frame_numbers.append(frame_idx)
         
         # Calculate change from previous frame
         if previous_row is not None:
@@ -317,8 +423,8 @@ def extract_row_strip(video_path, y_row, output_path, change_threshold=0.01, rel
         previous_row = current_row
         frame_idx += 1
         
-        if frame_idx % 100 == 0:
+        if (frame_idx - start_frame) % 100 == 0:
-            print(f"Processed {frame_idx}/{total_frames} frames")
+            print(f"Processed {frame_idx - start_frame}/{end_frame - start_frame + 1} frames")
     
     cap.release()
     
@@ -333,8 +439,14 @@ def extract_row_strip(video_path, y_row, output_path, change_threshold=0.01, rel
             for j in range(start, end):
                 include_mask[j] = True
     
-    # Collect significant rows
+    # Collect significant rows with actual frame numbers
-    significant_rows = [row for i, row in enumerate(all_rows) if include_mask[i]]
+    significant_rows = []
+    significant_frame_numbers = []
+    for i, row in enumerate(all_rows):
+        if include_mask[i]:
+            significant_rows.append(row)
+            significant_frame_numbers.append(frame_numbers[i])
+    
     included_frames = sum(include_mask)
     skipped_frames = len(all_rows) - included_frames
     
@@ -345,9 +457,13 @@ def extract_row_strip(video_path, y_row, output_path, change_threshold=0.01, rel
     strip_image = np.stack(significant_rows, axis=0)
     
     # Rotate clockwise 90 degrees for row mode
-    strip_image = cv2.rotate(strip_image, cv2.ROTATE_90_CLOCKWISE)
+    strip_image = cv2.rotate(strip_image, cv2.ROTATE_90_COUNTERCLOCKWISE)
     
-    print(f"Original frames: {total_frames}")
+    # Add timeline overlay if requested (after rotation)
+    if timeline:
+        strip_image = add_timeline_overlay(strip_image, significant_frame_numbers)
+    
+    print(f"Original frames in segment: {len(all_rows)}")
     print(f"Included frames: {included_frames}")
     print(f"Skipped frames: {skipped_frames}")
     print(f"Compression ratio: {skipped_frames/total_frames:.1%}")
@@ -402,6 +518,25 @@ def main():
         help="Include N extra frames before/after frames exceeding threshold (default: 0, or 100 if flag used without value)"
     )
     
+    parser.add_argument(
+        "--start",
+        type=int,
+        default=0,
+        help="Start frame number (0-based, default: 0)"
+    )
+    
+    parser.add_argument(
+        "--end",
+        type=int,
+        help="End frame number (0-based, default: last frame)"
+    )
+    
+    parser.add_argument(
+        "--timeline",
+        action="store_true",
+        help="Overlay frame numbers as timeline/ruler on output image"
+    )
+    
     parser.add_argument(
         "--debug",
         action="store_true",
@@ -440,6 +575,15 @@ def main():
         print("Error: --threshold must be between 0 and 1")
         sys.exit(1)
     
+    # Validate frame range
+    if args.start < 0:
+        print("Error: --start must be non-negative")
+        sys.exit(1)
+    
+    if args.end is not None and args.end < args.start:
+        print("Error: --end must be greater than or equal to --start")
+        sys.exit(1)
+    
     # Generate output path
     if args.output:
         output_path = Path(args.output)
@@ -469,20 +613,24 @@ def main():
             
             if args.xcolumn is not None:
                 print(f"Column mode: Analyzing vertical line at x={args.xcolumn}")
-                analyze_changes_only(video_path, x_column=args.xcolumn, debug_output=output_path)
+                analyze_changes_only(video_path, x_column=args.xcolumn, debug_output=output_path,
+                                   start_frame=args.start, end_frame=args.end)
             else:
                 print(f"Row mode: Analyzing horizontal line at y={args.yrow}")
-                analyze_changes_only(video_path, y_row=args.yrow, debug_output=output_path)
+                analyze_changes_only(video_path, y_row=args.yrow, debug_output=output_path,
+                                   start_frame=args.start, end_frame=args.end)
             
             print("Change analysis completed successfully!")
         else:
             # Normal mode: extract strip photography
             if args.xcolumn is not None:
                 print(f"Column mode: Extracting vertical line at x={args.xcolumn}")
-                extract_column_strip(video_path, args.xcolumn, output_path, args.threshold, args.relax)
+                extract_column_strip(video_path, args.xcolumn, output_path, args.threshold, args.relax, args.timeline,
+                                   args.start, args.end)
             else:
                 print(f"Row mode: Extracting horizontal line at y={args.yrow}")
-                extract_row_strip(video_path, args.yrow, output_path, args.threshold, args.relax)
+                extract_row_strip(video_path, args.yrow, output_path, args.threshold, args.relax, args.timeline,
+                                args.start, args.end)
             
             print("Strip photography extraction completed successfully!")