Update README.md
Signed-off-by: David Rotermund <54365609+davrot@users.noreply.github.com>
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@ -74,4 +74,116 @@ print(test_data.shape) # -> (101, 101, 3, 101)
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write_video(frames=test_data, filename="test", fps=20.0)
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```
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## Read the data from a mp4 file
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```python
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import numpy as np
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import cv2 # type: ignore
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def read_video(filename: str, display: bool = False) -> np.ndarray:
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assert len(filename) > 0, "read_video: Filename is empty."
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frames: np.ndarray = np.array([])
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cap = cv2.VideoCapture(filename)
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assert cap.isOpened() is True, "read_video: Error opening video stream or file!"
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n: int = int(cap.get(cv2.CAP_PROP_FRAME_COUNT))
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x: int = int(cap.get(cv2.CAP_PROP_FRAME_WIDTH))
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y: int = int(cap.get(cv2.CAP_PROP_FRAME_HEIGHT))
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print(f"Reading {n} frames with {x} x {y} pixels.")
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frames = np.zeros((y, x, 3, n)).astype(np.uint8)
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i: int = 0
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while cap.isOpened():
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ret, frame = cap.read()
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if ret is True:
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frames[:, :, :, i] = frame
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i += 1
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if display is True:
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cv2.imshow("Reading", frame)
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cv2.waitKey(25)
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else:
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break
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cap.release()
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if display is True:
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cv2.destroyWindow("Reading")
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return frames
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movie = read_video("test.mp4", display=True)
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print(movie.shape) # -> (100, 100, 3, 101)
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```
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## Playback a video
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```python
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import numpy as np
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import cv2 # type: ignore
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import time
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def show_video(frames: np.ndarray, fps: float = 20.0) -> np.ndarray:
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assert frames.size > 0, "The frame is empty."
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assert frames.ndim == 4, "The frame has wrong dimensions."
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n: int = frames.shape[3]
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dt: float = 1 / fps
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t: np.ndarray = np.zeros((n + 1))
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t[0] = time.perf_counter()
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for i in range(n):
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frame = frames[:, :, :, i]
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cv2.imshow("Display", frame)
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t_wait: float = t[i] + dt - time.perf_counter()
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retval = cv2.waitKey(int(max(1, 1000 * t_wait)))
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t[i + 1] = time.perf_counter()
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if retval != -1:
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break
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cv2.destroyWindow("Display")
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return t
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# Create test data
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axis_x = np.arange(-50, 51)[:, np.newaxis, np.newaxis] / 50
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axis_y = np.arange(-50, 51)[np.newaxis, :, np.newaxis] / 50
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axis_z = np.arange(-50, 51)[np.newaxis, np.newaxis, :] / 50
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test_data = np.sqrt(axis_x**2 + axis_y**2 + axis_z**2) < 0.75
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# Adding an additional axis for the color channel
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test_data = test_data[:, :, :, np.newaxis]
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test_data = np.tile(test_data, (1, 1, 1, 3))
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test_data = test_data.astype(dtype=np.float32)
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# Put the time axis as last axis
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test_data = np.moveaxis(test_data, 0, -1)
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# Conversion to uint8
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test_data -= test_data.min()
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test_data /= test_data.max()
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test_data *= 255
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test_data = test_data.astype(dtype=np.uint8)
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print(test_data.shape) # -> (101, 101, 3, 101)
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timings = show_video(frames=test_data, fps=20.0)
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print(timings.shape) # -> (102,)
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```
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