| """Metrics are fidelity/artifact proxies; none certifies plausible color by itself.""" |
| import numpy as np |
| import torch |
|
|
| def soft_ce(logits, idx, weights, class_weights=None): |
| |
| logits=logits.float() |
| idx=idx.permute(0,3,1,2) |
| weights=weights.permute(0,3,1,2) |
| nll=-((logits.gather(1,idx)-logits.logsumexp(1,keepdim=True))*weights).sum(1) |
| if class_weights is not None: |
| nll=nll*class_weights[idx[:,0]] |
| return nll.mean() |
|
|
| def per_image_metrics(L, pred, target): |
| error=(pred-target).square().sum(1).sqrt().mean((1,2)) |
| chroma=pred.square().sum(1).sqrt().mean((1,2)) |
| true_chroma=target.square().sum(1).sqrt().mean((1,2)) |
| seams=[] |
| for dim in [-1,-2]: |
| dp=pred.diff(dim=dim).square().sum(1).sqrt() |
| dt=target.diff(dim=dim).square().sum(1).sqrt() |
| dl=L.diff(dim=dim).abs()[:,0]*50 |
| |
| mask=(dl<2).float() |
| seams.append(((dp-dt).relu()*mask).sum((1,2))/mask.sum((1,2)).clamp_min(1)) |
| return {'ab_error':error,'chroma':chroma,'target_chroma':true_chroma, |
| 'excess_chroma_edge':sum(seams)/2} |
|
|
| def summarize(rows): |
| keys=['ce','ab_error','chroma','target_chroma','excess_chroma_edge'] |
| result={k:float(np.mean([r[k] for r in rows])) for k in keys} |
| result['n']=len(rows) |
| result['chroma_ratio']=result['chroma']/max(result['target_chroma'],1e-9) |
| return result |
|
|
