Spaces:
Running
on
L4
Running
on
L4
# Copyright (c) 2024 Bytedance Ltd. and/or its affiliates | |
# | |
# Licensed under the Apache License, Version 2.0 (the "License"); | |
# you may not use this file except in compliance with the License. | |
# You may obtain a copy of the License at | |
# | |
# http://www.apache.org/licenses/LICENSE-2.0 | |
# | |
# Unless required by applicable law or agreed to in writing, software | |
# distributed under the License is distributed on an "AS IS" BASIS, | |
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. | |
# See the License for the specific language governing permissions and | |
# limitations under the License. | |
import matplotlib.pyplot as plt | |
from latentsync.utils.util import count_video_time, gather_video_paths_recursively | |
from tqdm import tqdm | |
def plot_histogram(data, fig_path): | |
# Create histogram | |
plt.hist(data, bins=30, edgecolor="black") | |
# Add titles and labels | |
plt.title("Histogram of Data Distribution") | |
plt.xlabel("Video time") | |
plt.ylabel("Frequency") | |
# Save plot as an image file | |
plt.savefig(fig_path) # Save as PNG file. You can also use 'histogram.jpg', 'histogram.pdf', etc. | |
def main(input_dir, fig_path): | |
video_paths = gather_video_paths_recursively(input_dir) | |
video_times = [] | |
for video_path in tqdm(video_paths): | |
video_times.append(count_video_time(video_path)) | |
plot_histogram(video_times, fig_path) | |
if __name__ == "__main__": | |
input_dir = "validation" | |
fig_path = "histogram.png" | |
main(input_dir, fig_path) | |