| This dataset contains both 8 and 16 sampled frames of the "eating-spaghetti" video of the Kinetics-400 dataset, with the following frame indices being used: | |
| * 8 frames (`eating_spaghetti_8_frames.npy`): [ 97, 98, 99, 100, 101, 102, 103, 104] (NumPy seed was 1024, clip_len=8, frame_sample_rate=1, seg_len=len(vr)) | |
| * 16 frames (`eating_spaghetti.npy`): [164, 168, 172, 176, 181, 185, 189, 193, 198, 202, 206, 210, 215, 219, 223, 227]. | |
| * 32 frames (`eating_spaghetti_32_frames.npy`): array([ 47, 51, 55, 59, 63, 67, 71, 75, 80, 84, 88, 92, 96, | |
| 100, 104, 108, 113, 117, 121, 125, 129, 133, 137, 141, 146, 150, | |
| 154, 158, 162, 166, 170, 174]) (NumPy seed was 0, clip_len=32, frame_sample_rate=4, seg_len=len(vr)) | |
| This is the code: | |
| ``` | |
| from decord import VideoReader, cpu | |
| from huggingface_hub import hf_hub_download | |
| import numpy as np | |
| file_path = hf_hub_download( | |
| repo_id="nielsr/video-demo", filename="eating_spaghetti.mp4", repo_type="dataset" | |
| ) | |
| vr = VideoReader(file_path, num_threads=1, ctx=cpu(0)) | |
| # get 16 frames | |
| vr.seek(0) | |
| indices = [164 168 172 176 181 185 189 193 198 202 206 210 215 219 223 227] | |
| video = vr.get_batch(indices).asnumpy() | |
| # save as NumPy array | |
| with open('eating_spaghetti.npy', 'wb') as f: | |
| np.save(f, video) | |
| ``` |