اكتشاف الحركة بالتدفق البصري

import matplotlib.pyplot as plt
import numpy as np

frames = []
for frame_index in range(80):
    frame = np.zeros((96, 128), dtype=np.float32)
    if 12 <= frame_index < 68:
        start = 8 + frame_index
        frame[38:54, start:start + 16] = 1.0
    frames.append(frame)

fig, axes = plt.subplots(1, 3, figsize=(9, 3))
for axis, index in zip(axes, (0, 30, 70)):
    axis.imshow(frames[index], cmap="gray", vmin=0, vmax=1)
    axis.set_title(f"Frame {index}")
    axis.axis("off")
plt.tight_layout()

frame_differences = [np.abs(current - previous) for previous, current in zip(frames[:-1], frames[1:])]
motion_energy = np.asarray([difference.sum() for difference in frame_differences])
plt.plot(motion_energy)
plt.title("Frame-to-frame motion energy")
plt.xlabel("Frame")

threshold = max(1.0, float(motion_energy.max()) * 0.25)
active_frames = np.flatnonzero(motion_energy > threshold)
segments = []
if len(active_frames):
    start = previous = int(active_frames[0])
    for frame_index in active_frames[1:]:
        frame_index = int(frame_index)
        if frame_index != previous + 1:
            segments.append((start, previous + 1))
            start = frame_index
        previous = frame_index
    segments.append((start, previous + 1))
print(f"Detected motion segments: {segments}")

if not segments:
    raise RuntimeError("The generated motion fixture should contain one active segment")
segment_start, segment_stop = segments[0]
representative = (segment_start + segment_stop) // 2
plt.imshow(frames[representative], cmap="gray", vmin=0, vmax=1)
plt.title(f"Representative active frame {representative}")
plt.axis("off")