1. rcrnstn/zoommotion
  2. Commit 2a5c1078077bf592b1564176b9cc47894356f43b
Browse code

Add implementation

Robert Cranston authored on 02/06/2020 01:27:51
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README.md
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 Zoom in on video motion.
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+-   [Usage](#usage)
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+-   [Install](#install)
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+    -   [With `pipx`, for users](#with-pipx-for-users)
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+    -   [Into `venv`, for developers](#into-venv-for-developers)
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+-   [License](#license)
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+
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+`zoommotion` is implemented in [Python][], uses [OpenCV][] and [SciPy][] for
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+processing, and external [FFmpeg][] processes for broad file read and write
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+support (via [`ffmpeg-python`][] and [`pyffstream`][]).
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+
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+Simple algorithms are used to achieve speed with acceptable results ([Gaussian
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+mixture background/foreground segmentation][] and [Gaussian blur][] paired with
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+a [Butterworth filter][]). Algorithm parameters and input/output file
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+parameters can be supplied with command line options, see [Usage](#usage).
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+
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 [`zoommotion`]: https://git.rcrnstn.net/rcrnstn/zoommotion
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+[Python]: https://www.python.org
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+[OpenCV]: https://opencv.org/about/
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+[SciPy]: https://www.scipy.org
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+[FFmpeg]: https://ffmpeg.org
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+[`ffmpeg-python`]: https://github.com/kkroening/ffmpeg-python
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+[`pyffstream`]: https://git.rcrnstn.net/rcrnstn/pyffstream
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+[Gaussian mixture background/foreground segmentation]: https://docs.opencv.org/3.4/d7/d7b/classcv_1_1BackgroundSubtractorMOG2.html
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+[Gaussian blur]: https://docs.opencv.org/3.4/d4/d86/group__imgproc__filter.html#gaabe8c836e97159a9193fb0b11ac52cf1
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+[Butterworth filter]: https://docs.scipy.org/doc/scipy/reference/generated/scipy.signal.butter.html
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+
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+## Usage
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+
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+`zoommotion --help`:
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+
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+```
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+usage: zoommotion [-h] [--margins L R T B] [--blur-factor F]
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+                  [--blur-threshold T] [--lowpass-factor F]
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+                  [--start-frame FRAME] [--end-frame FRAME] [--decimate COUNT]
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+                  [--width WIDTH] [--height HEIGHT] [--codec CODEC]
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+                  [--pix-fmt PIX_FMT] [--extra-args ARGS] [--no-preview]
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+                  [--no-write] [--no-audio] [--overwrite] [--debug DEBUG_FILE]
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+                  [--output OUTPUT_FILE]
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+                  INPUT_FILE
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+
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+Zoom in on video motion.
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+
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+positional arguments:
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+  INPUT_FILE            input file
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+
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+optional arguments:
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+  -h, --help            show this help message and exit
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+  --margins L R T B     margins (left, right, top, bottom, in percent) of
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+                        output video (default: [0, 0, 0, 0])
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+  --blur-factor F       blur size factor (default: 0.05)
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+  --blur-threshold T    blur threshold (default: 32)
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+  --lowpass-factor F    low-pass filter cutoff frequency factor (default:
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+                        0.00015)
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+  --start-frame FRAME   starting input frame to process (inclusive)
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+  --end-frame FRAME     ending input frame to process (exclusive)
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+  --decimate COUNT      only use every COUNT input frame
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+  --width WIDTH         width of output video
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+  --height HEIGHT       height of output video
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+  --codec CODEC         codec of output video
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+  --pix-fmt PIX_FMT     pixel format of output video
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+  --extra-args ARGS     extra arguments to pass to FFmpeg, as a JSON object
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+                        (do not specify the leading dash for keys, use a null
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+                        value for arguments that do not take a parameter)
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+  --no-preview          do not show any previews
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+  --no-write            do not write any files
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+  --no-audio            do not include audio in output files
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+  --overwrite           overwrite output files
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+  --debug DEBUG_FILE    produce debug output (leave empty to base filename on
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+                        input)
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+  --output OUTPUT_FILE  produce final output (leave empty to base filename on
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+                        input)
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+```
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7 78 
 ## Install
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zoommotion.py
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+#!/usr/bin/env python3
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+
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+"""
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+Zoom in on video motion.
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+"""
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+
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+import pyffstream
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+import numpy as np
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+import PIL.Image
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+import cv2
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+import scipy.signal
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+
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+
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+def args_pre(parser):
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+    # Add arguments.
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+    parser.add_argument(
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+        '--margins', metavar=('L', 'R', 'T', 'B'), type=float, nargs=4,
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+        default=[0, 0, 0, 0],
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+        help="""
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+        margins (left, right, top, bottom, in percent) of output video
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+        (default: %(default)s)
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+        """)
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+    parser.add_argument(
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+        '--blur-factor', metavar='F', type=float, default=0.05,
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+        help="blur size factor (default: %(default)s)")
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+    parser.add_argument(
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+        '--blur-threshold', metavar='T', type=int, default=32,
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+        help="blur threshold (default: %(default)s)")
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+    parser.add_argument(
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+        '--lowpass-factor', metavar='F', type=float, default=0.00015,
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+        help="low-pass filter cutoff frequency factor (default: %(default)s)")
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+
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+
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+def init(args):
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+    # Set arguments.
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+    args.history = int(30 * args.output_fps)
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+    args.blur_size = (
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+        int(np.ceil(args.working_width * args.blur_factor)) // 2 * 2 + 1
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+    )
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+    args.lost_size = args.working_width * args.working_height * 0.001
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+    args.b, args.a = scipy.signal.butter(
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+        1, args.working_width / args.output_fps * args.lowpass_factor
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+    )
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+    args.history_track_ratio = 0.025
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+    args.resample_ratios = [
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+        # (1.0, PIL.Image.NEAREST),
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+        (0.5, PIL.Image.BILINEAR),
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+        (0.2, PIL.Image.BICUBIC),
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+        (0.0, PIL.Image.LANCZOS),
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+    ]
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+
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+    # Set state.
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+    class State:
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+        pass
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+    state = State()
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+    state.background_subtractor = cv2.createBackgroundSubtractorMOG2(
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+        history=args.history
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+    )
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+    state.filter_state = []
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+    return state
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+
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+
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+def process(args, state, frame, frame_num):
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+    # Create debug frame.
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+    if args.debug:
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+        debug_frame = frame.copy()
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+    else:
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+        debug_frame = None
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+
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+    # Subtract background, blur and threshold.
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+    foreground = state.background_subtractor.apply(frame)
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+    mask = cv2.compare(
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+        cv2.GaussianBlur(foreground, (args.blur_size, args.blur_size), 0),
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+        args.blur_threshold,
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+        cv2.CMP_GE,
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+    )
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+    if args.debug:
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+        debug_frame[mask > 0] = (0, 255, 0)
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+        debug_frame[foreground > 0] = (255, 0, 0)
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+
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+    # Nothing interesting?
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+    if np.count_nonzero(mask) < args.lost_size:
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+        # Reset rectangle.
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+        x, y, w, h = 0, 0, args.working_width, args.working_height
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+    else:
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+        # Find bounding rectangle.
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+        x, y, w, h = cv2.boundingRect(mask)
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+    if args.debug:
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+        cv2.rectangle(
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+            debug_frame, (x, y), (x+w, y+h), (0, 255, 0), 2 * args.thickness
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+        )
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+
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+    # Add rectangle margins.
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+    ml, mr, mt, mb = args.margins
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+    m = max(w, h)
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+    x = max(x - int(m * ml / 100), 0)
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+    y = max(y - int(m * mt / 100), 0)
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+    w = min(w + int(m * (ml+mr) / 100), args.working_width - x)
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+    h = min(h + int(m * (mt+mb) / 100), args.working_height - y)
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+    if args.debug:
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+        cv2.rectangle(
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+            debug_frame, (x, y), (x+w, y+h), (0, 0, 255), 2 * args.thickness
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+        )
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+
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+    # Filter rectangle.
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+    x1, y1, x2, y2 = x, y, x+w, y+h
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+    if frame_num == args.start_frame:
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+        state.filter_state = [
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+            coord * scipy.signal.lfilter_zi(args.b, args.a)
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+            for coord in (x1, y1, x2, y2)
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+        ]
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+    (x1, y1, x2, y2), filter_state_next = zip(*(
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+        scipy.signal.lfilter(args.b, args.a, [coord], zi=zi)
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+        for coord, zi in
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+        zip((x1, y1, x2, y2), state.filter_state)
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+    ))
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+    if frame_num >= args.start_frame + args.history * args.history_track_ratio:
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+        state.filter_state = filter_state_next
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+    x1, y1, x2, y2 = [int(coord[0]) for coord in (x1, y1, x2, y2)]
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+    x, y, w, h = x1, y1, x2-x1, y2-y1
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+    if args.debug:
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+        cv2.rectangle(
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+            debug_frame, (x, y), (x+w, y+h), (255, 0, 255), 2 * args.thickness
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+        )
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+
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+    # Fix rectangle.
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+    x, y, w, h = pyffstream.fix_rect(args, x, y, w, h)
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+
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+    # Determine resampling method.
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+    for i, (ratio, resample) in enumerate(args.resample_ratios):
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+        if min(w / args.output_width, h / args.output_height) >= ratio:
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+            break
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+    if args.debug:
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+        color_coeff = i / max(1, len(args.resample_ratios) - 1)
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+        color = (
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+            255 * (0 + color_coeff),
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+            255 * (1 - color_coeff),
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+            0,
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+        )
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+        cv2.rectangle(
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+            debug_frame, (x, y), (x+w, y+h), color, 2 * args.thickness,
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+        )
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+
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+    # Cut and resize.
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+    output_frame = pyffstream.resize(
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+        frame[y:y+h, x:x+w], args.output_width, args.output_height, resample
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+    )
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+
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+    # Return.
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+    return output_frame, debug_frame
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+
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+
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+def main():
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+    pyffstream.run(__doc__, process, init, args_pre)
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+
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+
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+if __name__ == '__main__':
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+    main()