User guide of the 5 datasets used in StableKeypoints:
Recently, I came across an intriguing project called StableKeypoints, which was published at CVPR 2024.
I attempted to run the project using its dataset but encountered some issues with almost every dataset.
After searching for solutions on the website and experimenting with the code, I managed to resolve most of these problems.
To make it more convenient for myself and others in the future, I am compiling some useful resources here.
Different datasets almost have the same time consuming for optimization embedding.
Because the iteration numbers is num_steps * (batch_size // num_gpus), which means the dataset size doesn't affect the iteration numbers.
The default batch_size is 4, so num_gpus must less than or equal to 4.
Commonly, num_gpus is 4, so the total iterations are num_steps * 4 // 4 = num_steps.
num_steps default is 500.
In practical experiments, the time consuming for optimization embedding about 20~30 minutes, affected by the status of the gpu (busy or idle).
- celeba: 19 minutes
- cub: 31 minutes
- deepfashion: 19 minutes
- human36m: 20 minutes
- taichi: 32 minutes
| Dataset | Train | Test |
|---|---|---|
| taichi | 5000 | 300 |
| cub_aligned | 5964 | 2874 |
| cub_001 | 29 | 17 |
| cub_002 | 30 | 14 |
| cub_003 | 30 | 15 |
| cub_all | 5964 | 2874 |
| deepfashion | 10604 | 1179 |
| celeba_aligned | 19000 | 1000 |
| celeba_wild | 5379 | 283 |
| human3.6m | 796648 | 87975 |
| unaligned_human3.6m | 159444 | 17615 |
The iteration depends on min(len(dataset), max_num_points).
The dataset here means the training set. And max_num_points is 50000.
Different datasets have different sizes, so the iteration numbers may vary.
| Dataset | Time | Images |
|---|---|---|
| taichi | 2 hours | 5000 |
| cub | 4 hours | 5964 |
| deepfashion | 7 hours | 10604 |
| celeba | 9.3 hours | 19000 |
| human36m | 22 hours | 50000 (actually 796648) |
The iteration is exactly on len(test dataset).
So it will totally depends on the size of the test dataset.
| Dataset | Time | Images |
|---|---|---|
| taichi | 0.1 hours | 300 |
| celeba | 0.5 hours | 1000 |
| deepfashion | 1 hour | 1179 |
| cub | 2 hours | 2874 |
| human36m | - | 87975 |