| |
| """Inspect the new reader against RGB without recomputing labels or MANO meshes. |
| |
| Displays object coordinate origins and MANO translation anchors, NOT masks or |
| hand joints. Optional old-reader comparison checks displayed pixels exactly. |
| """ |
| import argparse |
| import hashlib |
| import json |
| from pathlib import Path |
| import subprocess |
|
|
| import numpy as np |
| from PIL import Image, ImageDraw |
| import torch |
|
|
| from hot3d_bundle import Reader, at, fields |
|
|
|
|
| def project(points, params, max_angle): |
| """Same Fisheye624 diagnostic formula as pinned v1.0 fresh_sequence_common.""" |
| xyz=np.asarray(points,dtype=np.float64) |
| uv=np.full((len(xyz),2),np.nan) |
| good=np.isfinite(xyz).all(1)&(xyz[:,2]>1e-6) |
| p=np.asarray(params);xy=xyz[good,:2]/xyz[good,2,None] |
| r=np.linalg.norm(xy,axis=1);th=np.arctan(r) |
| radial=th*(1+sum(p[3+i]*th**(2*i+2) for i in range(6))) |
| xy=xy*np.divide(radial,r,out=np.ones_like(r),where=r>1e-12)[:,None] |
| x,y=xy.T;rr=x*x+y*y |
| xd=x+(2*x*x+rr)*p[9]+2*x*y*p[10]+p[11]*rr+p[12]*rr*rr |
| yd=y+(2*y*y+rr)*p[10]+2*x*y*p[9]+p[13]*rr+p[14]*rr*rr |
| uv[good]=p[0]*np.stack([xd,yd],1)+p[1:3] |
| angle=np.arctan2(np.linalg.norm(xyz[:,:2],axis=1),xyz[:,2]) |
| uv[angle>max_angle]=np.nan |
| return uv |
|
|
|
|
| def anchors(meta, tensors, index): |
| points=[];names=[];colors=[] |
| if 'mano' in tensors: |
| data,valid=tensors['mano'] |
| for side,(name,color) in enumerate([('L trans',(255,80,110)),('R trans',(70,210,255))]): |
| if valid[index,side]:points.append(data[index,side,58:61]);names.append(name);colors.append(color) |
| for name,(data,valid) in tensors.items(): |
| if name.startswith('object_') and name.endswith('_pose') and valid[index]: |
| points.append(data[index,:3,3]);names.append(name[7:-5][-5:]);colors.append((245,215,65)) |
| return np.asarray(points).reshape(-1,3),names,colors |
|
|
|
|
| def draw(rgb, xy, names, colors): |
| image=Image.fromarray(rgb.copy());d=ImageDraw.Draw(image) |
| for (x,y),name,color in zip(xy,names,colors): |
| if not np.isfinite([x,y]).all() or not (0<=x<image.width and 0<=y<image.height):continue |
| x,y=int(round(x)),int(round(y)) |
| d.ellipse((x-5,y-5,x+5,y+5),outline=color,width=3);d.text((x+7,y),name,fill=color) |
| return image |
|
|
|
|
| def run(view,video,out,source=None): |
| torch.set_num_threads(1);view=Path(view);out=Path(out);out.mkdir(parents=True,exist_ok=True) |
| reader=Reader(view);meta=reader.meta;total=meta['num_frames'];w,h=meta['camera']['image_size'] |
| new={};old={};before=json.loads((Path(source)/'metainfo.json').read_text()) if source else None |
| for field in fields(meta): |
| if len(field['locator'])!=2:continue |
| name=field['locator'][1];new[name]=tuple(x.numpy() for x in reader.numeric(field)) |
| if source: |
| c=at(before,field['locator']);old[name]=tuple(torch.load(Path(source)/c[k],map_location='cpu',weights_only=True).numpy() for k in ['data_ref','valid_ref']) |
| indices=sorted({0,1,total//4,total//2,3*total//4,total-1}) |
| |
| command=['ffmpeg','-nostdin','-v','error','-threads','1','-noautorotate','-i',str(video), |
| '-map','0:v:0','-fps_mode','passthrough','-f','rawvideo','-pix_fmt','rgb24','-threads','1','pipe:1'] |
| decoded_sha=hashlib.sha256();rows=[];count=0 |
| with (out/'decode.log').open('w') as log: |
| proc=subprocess.Popen(command,stdout=subprocess.PIPE,stderr=log) |
| try: |
| while True: |
| chunk=proc.stdout.read(w*h*3) |
| if not chunk:break |
| if len(chunk)!=w*h*3:raise ValueError('Truncated decoded frame') |
| decoded_sha.update(chunk) |
| if count in indices: |
| rgb=np.frombuffer(chunk,np.uint8).reshape(h,w,3) |
| points,names,colors=anchors(meta,new,count) |
| uv=project(points,new['intrinsic'][0][count],meta['camera']['max_solid_angle']) |
| revised=draw(rgb,uv,names,colors) |
| if source: |
| oldpoints,oldnames,oldcolors=anchors(before,old,count) |
| olduv=project(oldpoints,old['intrinsic'][0][count],before['camera']['max_solid_angle']) |
| previous=draw(rgb,olduv,oldnames,oldcolors) |
| if previous.tobytes()!=revised.tobytes():raise ValueError('Old/new diagnostic pixels differ') |
| else:previous=Image.fromarray(rgb) |
| panels=[Image.fromarray(rgb),previous,revised] |
| cell=480;scaled_h=round(h*cell/w);canvas=Image.new('RGB',(3*cell,scaled_h+70),(245,245,245));d=ImageDraw.Draw(canvas) |
| for col,(im,title) in enumerate(zip(panels,['RGB unchanged','v1.0 anchors' if source else 'RGB unchanged','v1.1 anchors'])): |
| d.text((col*cell+8,8),title,fill=(20,20,20));canvas.paste(im.resize((cell,scaled_h)),(col*cell,30)) |
| d.text((8,scaled_h+36),f"{meta['sequence_id']} / {meta['camera_id']} frame {count}; anchors only, NOT segmentation or hand joints",fill=(20,20,20)) |
| name=f'frame-{count:06d}.png';canvas.save(out/name) |
| rows.append({'frame_index':count,'path':name,'old_new_preview_pixels_equal':bool(source),'visible_anchors':len(points)}) |
| count+=1 |
| proc.stdout.close() |
| if proc.wait()!=0:raise RuntimeError('Video decoding failed; see decode.log') |
| finally: |
| if proc.poll() is None:proc.terminate();proc.wait() |
| if count!=total:raise ValueError(f'RGB frames {count} != metainfo {total}') |
| report={'sequence':meta['sequence_id'],'camera':meta['camera_id'],'decoded_frames':count,'dimensions':[w,h], |
| 'decoded_rgb_sha256':decoded_sha.hexdigest(),'new_reader_used':True,'all_frames_decoded':True, |
| 'source_numeric_comparison':bool(source),'panels':rows,'not_segmentation_quality_review':True} |
| (out/'report.json').write_text(json.dumps(report,indent=2)+'\n') |
| print(json.dumps({k:v for k,v in report.items() if k!='panels'},indent=2)) |
| return report |
|
|
|
|
| def main(): |
| p=argparse.ArgumentParser(description=__doc__);p.add_argument('view',type=Path) |
| p.add_argument('--video',type=Path);p.add_argument('--output',type=Path,required=True);p.add_argument('--source',type=Path) |
| a=p.parse_args();run(a.view,a.video or a.view/'observation/rgb.mkv',a.output,a.source) |
|
|
|
|
| if __name__=='__main__':main() |
|
|
