YAML Metadata Warning:empty or missing yaml metadata in repo card
Check out the documentation for more information.
PolarFree PSD 4-channel Weights
Pre-trained weights for PolarFree model trained on PSD (Polarization Specular Dataset).
Important: 4-channel Polarization Format
PSD dataset originally has 12 polarization angles (30Β° intervals), but these weights were trained with 4-channel format (0Β°, 45Β°, 90Β°, 135Β°) to match standard polarization camera output.
Angle Conversion
PSD 12 angles β 4 angles:
- 0Β° β idx-01 (direct)
- 45Β° β interpolate(idx-02, idx-03)
- 90Β° β idx-04 (direct)
- 135Β° β interpolate(idx-05, idx-06)
Model Structure
stage1/
βββ net_g_100000.pth # Generator (72MB)
βββ net_le_100000.pth # Latent Encoder (2.5MB)
stage2/
βββ net_g_50000.pth # Generator (72MB)
βββ net_le_dm_50000.pth # Latent Encoder DM (2.4MB)
βββ net_d_50000.pth # Denoising Network (10MB)
Performance
Test Set (50 samples)
| Stage | Iteration | PSNR (dB) | SSIM |
|---|---|---|---|
| Stage 1 | 100,000 | 34.85 | 0.9918 |
| Stage 2 | 50,000 | 34.45 | 0.9914 |
Inference Time (512x768)
| Stage | GPU (RTX 6000) | CPU |
|---|---|---|
| Stage 1 | 325 ms | ~31 sec |
| Stage 2 | 271 ms | ~22 sec |
Usage
from huggingface_hub import hf_hub_download
import torch
# Download Stage 1 weights
net_g_path = hf_hub_download(
repo_id="nawta/PolarFree-PSD-4ch-weights",
filename="stage1/net_g_100000.pth"
)
# Load
checkpoint = torch.load(net_g_path)
model.load_state_dict(checkpoint["params"])
License
Private repository - for research use only.
Inference Providers NEW
This model isn't deployed by any Inference Provider. π Ask for provider support