scripts: rewrite append_signals.py for linescan scrolling video
Complete rewrite to properly handle linescan image sequences: - Stitches linescan images horizontally into wide panorama - Creates scrolling video that pans left-to-right - Configurable scroll speed based on capture rate (750 lines/sec) - Output saved one folder up from image source - Uses Pillow for image stitching, ffmpeg for video creation Features: - --scroll-speed: multiplier for playback speed (1.0 = real-time) - --lines-per-second: linescan capture rate (default: 750) - --max-frames: limit frames for testing - --fps: output video framerate (default: 30) - --width: viewport width (default: 1920) - Automatic cleanup of temporary stitched image Example usage: # Real-time playback uv run scripts\append_signals.py results\20251122\bumpy-filter # 2x speed uv run scripts\append_signals.py results\20251122\bumpy-filter --scroll-speed 2.0 # Test with 10 frames uv run scripts\append_signals.py results\20251122\bumpy-filter --max-frames 10
This commit is contained in:
yair
@@ -1,12 +1,14 @@
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#!/usr/bin/env -S uv run
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# /// script
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# requires-python = ">=3.10"
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# dependencies = []
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# dependencies = [
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# "pillow",
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# ]
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# ///
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"""
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Concatenate a sequence of frames into a video using ffmpeg.
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Scales to 1920 width and allows control of video speed via fps.
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Stitch linescan frame sequences horizontally and create scrolling video.
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Linescan images are concatenated side-by-side and played as a scrolling video.
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"""
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import argparse
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@@ -15,6 +17,7 @@ import sys
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import time
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from pathlib import Path
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from typing import List
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from PIL import Image
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def find_frames(directory: Path, pattern: str = "*.jpeg") -> List[Path]:
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@@ -27,83 +30,105 @@ def find_frames(directory: Path, pattern: str = "*.jpeg") -> List[Path]:
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return frames
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def create_video_ffmpeg(
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input_dir: Path,
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def stitch_images_horizontally(
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frames: List[Path],
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output_file: Path,
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fps: int = 30,
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width: int = 1920,
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crf: int = 18,
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pattern: str = "*.jpeg",
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max_frames: int = None
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) -> None:
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) -> tuple[int, int]:
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"""
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Create video from image sequence using ffmpeg.
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Args:
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input_dir: Directory containing the frames
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output_file: Output video file path
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fps: Frames per second (controls playback speed)
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width: Output video width in pixels (height auto-scales)
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crf: Constant Rate Factor for quality (lower = better, 18-23 recommended)
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pattern: File pattern to match frame files
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Stitch images horizontally into a single wide image.
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Returns (width, height) of stitched image.
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"""
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frames = find_frames(input_dir, pattern)
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if not frames:
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print(f"Error: No frames found in {input_dir} matching pattern {pattern}")
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sys.exit(1)
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total_frames = len(frames)
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# Limit frames if max_frames is specified
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if max_frames is not None and max_frames > 0:
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frames = frames[:max_frames]
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print(f"Found {total_frames} frames in {input_dir}, processing first {len(frames)} frames")
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else:
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print(f"Found {len(frames)} frames in {input_dir}")
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print(f"First frame: {frames[0].name}")
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print(f"Last frame: {frames[-1].name}")
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# Check if frames are sequential (no gaps)
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first_frame = frames[0]
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is_sequential = True
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print(f"Loading {len(frames)} images for stitching...")
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# Extract frame numbers and check for gaps
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name_parts = first_frame.stem.rsplit('_', 1)
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if len(name_parts) == 2 and name_parts[1].isdigit():
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frame_numbers = []
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for frame in frames:
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parts = frame.stem.rsplit('_', 1)
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if len(parts) == 2 and parts[1].isdigit():
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frame_numbers.append(int(parts[1]))
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else:
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is_sequential = False
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break
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# Load first image to get dimensions
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first_img = Image.open(frames[0])
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img_width, img_height = first_img.size
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# Check if there are gaps in the sequence
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if is_sequential and frame_numbers:
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expected_count = frame_numbers[-1] - frame_numbers[0] + 1
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if len(frame_numbers) != expected_count:
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is_sequential = False
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print(f"Warning: Detected gaps in frame sequence (have {len(frame_numbers)} frames, expected {expected_count})")
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else:
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is_sequential = False
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# Calculate total width
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total_width = img_width * len(frames)
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# Use concat method for reliability (works with gaps, non-sequential naming, etc.)
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# Create concat file
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concat_file = input_dir / "concat_list.txt"
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with open(concat_file, 'w') as f:
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for frame in frames:
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# Use absolute paths to avoid issues
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f.write(f"file '{frame.absolute()}'\n")
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print(f"Creating stitched image: {total_width}x{img_height} pixels")
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print(f" Individual frame size: {img_width}x{img_height}")
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print(f" Total frames: {len(frames)}")
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# Create large canvas
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stitched = Image.new('RGB', (total_width, img_height))
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# Paste images
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x_offset = 0
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for i, frame_path in enumerate(frames):
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if i % 50 == 0:
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print(f" Stitching frame {i+1}/{len(frames)}...")
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img = Image.open(frame_path)
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stitched.paste(img, (x_offset, 0))
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x_offset += img_width
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print(f"Saving stitched image to {output_file}...")
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stitched.save(output_file, quality=95)
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return total_width, img_height
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def create_scrolling_video(
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stitched_image: Path,
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output_file: Path,
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total_width: int,
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height: int,
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output_width: int = 1920,
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scroll_speed: float = 750.0,
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fps: int = 30,
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crf: int = 18,
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lines_per_second: float = 750.0
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) -> None:
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"""
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Create scrolling video from stitched image.
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Args:
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stitched_image: Path to stitched horizontal image
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output_file: Output video file
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total_width: Total width of stitched image
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height: Height of image
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output_width: Width of output video viewport
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scroll_speed: Scroll speed multiplier (1.0 = real-time @ 750 lines/sec)
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fps: Output video framerate
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crf: Quality (lower = better)
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lines_per_second: Linescan capture rate (pixels per second)
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"""
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# Calculate scroll parameters
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# At scroll_speed=1.0, we scroll at the actual capture rate
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pixels_per_second = lines_per_second * scroll_speed
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pixels_per_frame = pixels_per_second / fps
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# Calculate video duration
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scrollable_width = total_width - output_width
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duration = scrollable_width / pixels_per_second
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total_frames = int(duration * fps)
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print(f"\nScrolling video parameters:")
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print(f" Output viewport: {output_width}x{height}")
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print(f" Scroll speed: {scroll_speed}x real-time ({pixels_per_second:.1f} pixels/sec)")
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print(f" Pixels per frame: {pixels_per_frame:.2f}")
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print(f" Video duration: {duration:.2f} seconds")
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print(f" Total frames: {total_frames}")
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print(f" Output FPS: {fps}")
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# FFmpeg crop filter with horizontal scrolling
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# crop=w:h:x:y where x moves from 0 to (total_width - output_width)
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# The 't' variable represents time in seconds
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crop_expr = f"crop={output_width}:{height}:min({pixels_per_second}*t\\,{total_width-output_width}):0"
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cmd = [
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"ffmpeg",
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"-y",
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"-f", "concat",
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"-safe", "0",
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"-i", str(concat_file),
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"-vf", f"scale={width}:-2,fps={fps}",
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"-loop", "1",
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"-i", str(stitched_image),
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"-vf", crop_expr,
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"-t", str(duration),
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"-r", str(fps),
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"-c:v", "libx264",
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"-crf", str(crf),
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"-pix_fmt", "yuv420p",
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@@ -111,20 +136,17 @@ def create_video_ffmpeg(
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str(output_file)
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]
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print(f"\nCreating video with:")
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print(f" FPS: {fps}")
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print(f" Width: {width}px")
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print(f" CRF (quality): {crf}")
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print(f" Output: {output_file}")
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print(f"\nRunning: {' '.join(cmd)}\n")
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print(f"\nRunning ffmpeg...")
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print(f"Command: {' '.join(cmd)}\n")
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try:
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result = subprocess.run(cmd, check=True)
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print(f"\n✓ Video created successfully: {output_file}")
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subprocess.run(cmd, check=True)
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print(f"\n✓ Scrolling video created successfully: {output_file}")
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# Show file size
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size_mb = output_file.stat().st_size / (1024 * 1024)
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print(f" File size: {size_mb:.2f} MB")
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print(f" Duration: {duration:.2f} seconds")
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except subprocess.CalledProcessError as e:
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print(f"Error: ffmpeg command failed with return code {e.returncode}")
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@@ -136,54 +158,68 @@ def create_video_ffmpeg(
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def main():
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parser = argparse.ArgumentParser(
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description="Concatenate frame sequences into a video using ffmpeg",
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description="Stitch linescan images horizontally and create scrolling video",
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formatter_class=argparse.RawDescriptionHelpFormatter,
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epilog="""
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Examples:
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# Basic usage with default settings (30 fps, 1920 width)
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python append_signals.py C:\\dev\\gst-plugins-vision\\results\\20251122\\bumpy-filter
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# Real-time playback (1.0x speed, 750 lines/second)
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python append_signals.py results/20251122/bumpy-filter
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# Slow motion (10 fps)
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python append_signals.py C:\\dev\\gst-plugins-vision\\results\\20251122\\bumpy-filter --fps 10
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# Slow motion (0.5x speed)
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python append_signals.py results/20251122/bumpy-filter --scroll-speed 0.5
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# Fast playback (60 fps) with custom output name
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python append_signals.py results/20251122/bumpy-filter --fps 60 -o timelapse.mp4
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# Fast playback (2x speed)
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python append_signals.py results/20251122/bumpy-filter --scroll-speed 2.0
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# Higher quality (lower CRF)
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python append_signals.py results/20251122/bumpy-filter --crf 15
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# Custom width
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python append_signals.py results/20251122/bumpy-filter --width 3840
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# Process only first 100 frames for testing
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# Process only first 100 frames
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python append_signals.py results/20251122/bumpy-filter --max-frames 100
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# Higher FPS for smoother scrolling
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python append_signals.py results/20251122/bumpy-filter --fps 60
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# Custom output width (4K)
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python append_signals.py results/20251122/bumpy-filter --width 3840
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"""
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)
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parser.add_argument(
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"input_dir",
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type=Path,
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help="Directory containing the frame sequence"
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help="Directory containing the linescan frame sequence"
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)
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parser.add_argument(
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"-o", "--output",
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type=Path,
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help="Output video file (default: output.mp4 in input directory)"
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help="Output video file (default: {folder_name}_{timestamp}.mp4 in input dir)"
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)
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parser.add_argument(
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"--scroll-speed",
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type=float,
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default=1.0,
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help="Scroll speed multiplier (1.0 = real-time at 750 lines/sec, default: 1.0)"
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)
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parser.add_argument(
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"--lines-per-second",
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type=float,
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default=750.0,
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help="Linescan capture rate in lines/pixels per second (default: 750)"
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)
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parser.add_argument(
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"--fps",
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type=int,
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default=30,
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help="Output video framerate/playback speed (default: 30)"
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help="Output video framerate (default: 30)"
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)
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parser.add_argument(
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"--width",
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type=int,
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default=1920,
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help="Output video width in pixels (default: 1920)"
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help="Output video viewport width in pixels (default: 1920)"
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)
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parser.add_argument(
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@@ -218,13 +254,26 @@ Examples:
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print(f"Error: Input path is not a directory: {args.input_dir}")
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sys.exit(1)
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# Set output file
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# Find frames
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frames = find_frames(args.input_dir, args.pattern)
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if not frames:
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print(f"Error: No frames found in {args.input_dir} matching pattern {args.pattern}")
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sys.exit(1)
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total_frames = len(frames)
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if args.max_frames is not None and args.max_frames > 0:
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frames = frames[:args.max_frames]
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print(f"Found {total_frames} frames, processing first {len(frames)} frames")
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else:
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print(f"Found {len(frames)} frames in {args.input_dir}")
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# Set output file (one folder up from input directory)
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if args.output is None:
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# Generate filename: input_folder_name_unixtime.mp4
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unix_time = int(time.time())
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folder_name = args.input_dir.name
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output_filename = f"{folder_name}_{unix_time}.mp4"
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output_file = args.input_dir / output_filename
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output_filename = f"{folder_name}_scroll_{unix_time}.mp4"
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output_file = args.input_dir.parent / output_filename
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else:
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output_file = args.output
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@@ -233,15 +282,36 @@ Examples:
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print("Error: CRF must be between 0 and 51")
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sys.exit(1)
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create_video_ffmpeg(
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input_dir=args.input_dir,
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output_file=output_file,
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fps=args.fps,
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width=args.width,
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crf=args.crf,
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pattern=args.pattern,
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max_frames=args.max_frames
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)
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# Create temporary stitched image
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stitched_filename = f"stitched_temp_{int(time.time())}.jpg"
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stitched_path = args.input_dir / stitched_filename
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try:
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# Stitch images
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total_width, img_height = stitch_images_horizontally(
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frames=frames,
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output_file=stitched_path,
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max_frames=args.max_frames
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)
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# Create scrolling video
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create_scrolling_video(
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stitched_image=stitched_path,
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output_file=output_file,
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total_width=total_width,
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height=img_height,
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output_width=args.width,
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scroll_speed=args.scroll_speed,
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fps=args.fps,
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crf=args.crf,
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lines_per_second=args.lines_per_second
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)
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finally:
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# Clean up temporary stitched image
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if stitched_path.exists():
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print(f"\nCleaning up temporary file: {stitched_filename}")
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stitched_path.unlink()
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if __name__ == "__main__":
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