def test_normalized_tensor_range_and_shape():
sigma = 1
smoothed_tensor = smooth_trajectory_tensor(tensor, sigma)
normalized_tensor = normalize_trajectory_tensor(smoothed_tensor)
assert smoothed_tensor.shape == normalized_tensor.shape
assert normalized_tensor.max() == 1
assert normalized_tensor.min() == 0
def test_correct_dimentions_smoothed():
sigma = 1
smoothed_tensor = smooth_trajectory_tensor(tensor, sigma)
# Camera dimention
assert np.all(tensor[0] != smoothed_tensor[0])
assert np.all(tensor[1] == smoothed_tensor[1])
# Time dimention
assert np.all(tensor[0][1] != smoothed_tensor[0][1])
def __getitem__(self, idx):
this_input = self.inputs[idx].astype(np.float32)
this_target = self.targets[idx]
if self.heatmap_smoothing_sigma != 0:
this_input = smooth_trajectory_tensor(this_input,
self.heatmap_smoothing_sigma)
this_input = normalize_trajectory_tensor(this_input)
return {"inputs": this_input, "targets": this_target}
def __getitem__(self, idx):
this_input = np.stack(self.inputs[idx], axis=0).astype(np.float32)
this_target = np.stack(self.targets[idx], axis=0)
if self.heatmap_smoothing_sigma != 0:
for target_num in range(this_input.shape[0]):
this_input[target_num] = smooth_trajectory_tensor(
this_input[target_num], self.heatmap_smoothing_sigma)
this_input[target_num] = normalize_trajectory_tensor(
this_input[target_num])
return {"inputs": this_input, "targets": this_target}
output_video = np.zeros((20, 1080, 1920, 3), dtype="uint8")
for camera_num in range(1, NUM_CAMERAS + 1):
print(camera_num)
video_path = os.path.join(
DATA_PATH,
"videos",
"day_" + str(args.day),
"departures",
"camera_" + str(camera_num),
"departure_" + str(args.match_number).zfill(3) + ".mp4",
)
video = utils.read_video(video_path)
video = utils.resize_video(video, (480, 270))
input_tensor = input_tensor.astype(float)
input_tensor = smooth_trajectory_tensor(input_tensor, 1)
input_tensor = normalize_trajectory_tensor(input_tensor)
for frame in range(10):
this_heatmap = input_tensor[camera_num - 1, frame]
this_heatmap = cv2.resize(this_heatmap,
dsize=(480, 270),
interpolation=cv2.INTER_NEAREST)
this_heatmap = 255 - (this_heatmap * 255)
this_heatmap = this_heatmap.astype("uint8")
this_heatmap = cv2.applyColorMap(this_heatmap, cmapy.cmap("coolwarm"))
video[frame + 10] = cv2.addWeighted(this_heatmap, 0.6,
video[frame + 10], 0.4, 0)
video[frame + 10] = utils.draw_grid(video[frame + 10], (27, 48), 1)
start_x = int(math.floor((camera_num - 1) / 4) * 270)
start_y = int(((camera_num - 1) % 4) * 480)