Datasets:
File size: 8,387 Bytes
7735593 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 | import json, pickle, hashlib, collections, random, itertools, math
from pathlib import Path
import numpy as np
import openpyxl
INSTRUMENTS=['grasper','bipolar','hook','scissors','clipper','irrigator']
TOOLS=INSTRUMENTS+['specimen_bag']
ANATOMIES=['gallbladder','liver','omentum','gut','cystic_plate']
VERBS=['grasp','retract','dissect','coagulate','clip','cut','aspirate','irrigate','pack']
GERUND={'grasp':'Grasping','retract':'Retracting','dissect':'Dissecting','coagulate':'Coagulating','clip':'Clipping','cut':'Cutting','aspirate':'Aspirating','irrigate':'Irrigating','pack':'Packing'}
PARTICIPLE={'grasp':'grasped','retract':'retracted','dissect':'dissected','coagulate':'coagulated','clip':'clipped','cut':'cut','aspirate':'aspirated','irrigate':'irrigated','pack':'packed'}
PHASES={0:'Preparation',1:'Calot triangle dissection',2:'Clipping and cutting',3:'Gallbladder dissection',4:'Gallbladder packaging',5:'Cleaning and coagulation',6:'Gallbladder retraction'}
QUADS=['Upper left','Upper right','Lower left','Lower right']
INV={'left':'right','right':'left','above':'below','below':'above'}
FAMILIES={'P':'Perception','R':'Relation','C':'Composition','PR':'Procedure','V':'CVS','D':'Dynamic'}
def display(x):return x.replace('_',' ')
def title(x):return display(x).capitalize()
def digest(x):return hashlib.sha256(json.dumps(x,sort_keys=True,separators=(',',':')).encode()).hexdigest()
def write_json(p,x):Path(p).parent.mkdir(parents=True,exist_ok=True);Path(p).write_text(json.dumps(x,ensure_ascii=False,indent=2))
def read_jsonl(p):
with open(p) as f:
for l in f:
if l.strip():yield json.loads(l)
def write_jsonl(p,rows):
Path(p).parent.mkdir(parents=True,exist_ok=True)
with open(p,'w') as f:
for r in rows:f.write(json.dumps(r,ensure_ascii=False,separators=(',',':'))+'\n')
def family(task):return FAMILIES[''.join(x for x in task if x.isalpha())]
class Sources:
def __init__(self,ori,videos):
self.ori=Path(ori);self.videos=videos;self.phase={};self.ivt={};self.graphs={};self.action_starts={};self.cvt={};self.counts=collections.Counter()
for fn in ['train/1fps_100_0.pickle','val/1fps.pickle','test/1fps.pickle']:
p=self.ori/' Cholec80_labels/labels'/fn
with p.open('rb') as f:d=pickle.load(f)
for key,rows in d.items():
v=int(key[5:])
if v in videos:
self.phase[v]=rows
assert all(int(r['Original_frame_id'])==i*25 for i,r in enumerate(rows)),('alignment',v)
vocab={int(a):tuple(b.split(',')) for line in (self.ori/'CholecT45/dict/triplet.txt').read_text().splitlines() for a,b in [line.split(':',1)]}
for v in videos:
self.ivt[v]={};starts={}
for line in (self.ori/f'CholecT45/triplet/VID{v:02d}.txt').read_text().splitlines():
row=list(map(int,line.split(',')));f=row[0];ts={vocab[i] for i,a in enumerate(row[1:]) if a}
for t in ts:
if t not in starts:starts[t]=f
self.action_starts[v,f,t]=starts[t]
starts={t:starts[t] for t in ts};self.ivt[v][f]=ts
for f in range(len(self.phase[v])):
p=self.ori/f'scene_graph/VID{v:02d}_{f}.json'
if p.exists():
try:self.graphs[v,f]=json.loads(p.read_text())['scenes'][0]
except (KeyError,IndexError,ValueError):self.counts['invalid_sg']+=1
self.cvs_rows=[]
ws=openpyxl.load_workbook(self.ori/'Cholec80_CVS/cholec80-CVS.xlsx',data_only=True).active
for i,row in enumerate(ws.values):
if not i or int(row[0]) not in videos:continue
r=dict(row=i+1,video=int(row[0]),start=int(row[2])*60+int(row[3]),end=int(row[4])*60+int(row[5]),scores=list(map(int,row[6:9])),total=int(row[9]),cv=int(row[1]))
assert sum(r['scores'])==r['total'] and int(r['total']>=5)==r['cv']
self.cvs_rows.append(r)
for v in videos:
first=next(i for i,r in enumerate(self.phase[v]) if r['Phase_gt']==2)
rs=[r for r in self.cvs_rows if r['video']==v and r['start']<=r['end']]
good={}
for f in range(first):
if self.phase[v][f]['Phase_gt']!=1:continue
rr=[r for r in rs if r['start']<=f<=r['end']];vals={tuple(r['scores']) for r in rr}
if len(vals)>1:self.counts['cvs_conflicting_seconds']+=1;continue
score=next(iter(vals)) if vals else (0,0,0)
good[f]=dict(scores=list(score),cv=int(sum(score)>=5),rows=[r['row'] for r in rr],source='explicit_interval' if rr else 'protocol_default_zero')
for k in range(4):
segments=[]
for f,r in good.items():
value=r['scores'][k] if k<3 else r['cv']
if segments and segments[-1]['end']==f-1 and segments[-1]['value']==value:segments[-1]['end']=f
else:segments.append(dict(start=f,end=f,value=value))
for seg in segments:
for f in range(seg['start'],seg['end']+1):
good[f][f'episode_{k}']=seg
self.cvt[v]=good
print('Source loaded',len(self.graphs),'graphs;',sum(len(x) for x in self.ivt.values()),'IVT frames',flush=True)
def image_path(self,v,f):return self.ori/f'CholecT45/data/VID{v:02d}/{f:06d}.png'
def tools(self,v,f):
t=self.phase[v][f]['Tool_gt']
return None if t is None else {TOOLS[i] for i,a in enumerate(t) if a}
def clean_objects(self,v,f):
g=self.graphs.get((v,f),{});out={}
for i,o in enumerate(g.get('objects',[])):
b=o.get('bbox');c=o.get('center')
if not b or not c or len(b)!=4:continue
x,y,X,Y=b
if not (0<=x<X<=430 and 0<=y<Y<=240):continue
if abs(c[0]-(x+X)/2)>0.01 or abs(c[1]-(y+Y)/2)>0.01:continue
w=X-x;h=Y-y
if o['type']=='instrument' and (w<15 or h<10 or w*h<450):continue
if o['type']=='anatomy' and (w<25 or h<18 or w*h<1000):continue
out[i]=o
return out
def unique(self,v,f):
objs=self.clean_objects(v,f);cnt=collections.Counter(o['component'] for o in self.graphs.get((v,f),{}).get('objects',[]))
return {o['component']:i for i,o in objs.items() if cnt[o['component']]==1}
def spatial(self,v,f,a,b,p,require_edge=True):
if a==b:return False
o=self.graphs[v,f]['objects'];axis=0 if p in ['left','right'] else 1
d=(o[a]['center'][axis]-o[b]['center'][axis])*(1 if p in ['right','below'] else -1)
if d<(.05*(430 if axis==0 else 240)):return False
if not require_edge:return True
r=self.graphs[v,f]['relationships'];return a in r.get(p,[[]]*len(o))[b] and b in r.get(INV[p],[[]]*len(o))[a]
def definite(self,v,f,a,b,p):
if a==b:return True
o=self.graphs[v,f]['objects'];axis=0 if p in ['left','right'] else 1
return abs(o[a]['center'][axis]-o[b]['center'][axis])>=.05*(430 if axis==0 else 240)
def consistent(self,v,f,a,b,p):
return self.definite(v,f,a,b,p) and (not self.spatial(v,f,a,b,p,False) or self.spatial(v,f,a,b,p,True))
def quadrant(self,v,f,a,b=None):
o=self.graphs[v,f]['objects'];x,y=o[a]['center'];X,Y=(215,120) if b is None else o[b]['center']
if abs(x-X)<21.5 or abs(y-Y)<12:return None
p='left' if x<X else 'right';q='above' if y<Y else 'below'
if b is not None and not (self.spatial(v,f,a,b,p) and self.spatial(v,f,a,b,q)):return None
return ('Upper' if y<Y else 'Lower')+(' left' if x<X else ' right')
def action_edge(self,v,f,inst,verb,target):
u=self.unique(v,f)
if inst not in u or target not in u:return False
g=self.graphs[v,f];return u[target] in g['relationships'].get(verb,[[]]*len(g['objects']))[u[inst]]
def source_evidence(self,v,frames):
out=[]
for f in frames:
r=self.phase[v][f];g=self.graphs.get((v,f))
out.append(dict(video=f'VID{v:02d}',frame_1fps=f,original_frame_id=int(r['Original_frame_id']),phase=int(r['Phase_gt']),tools=None if r['Tool_gt'] is None else list(map(int,r['Tool_gt'])),ivt=sorted(self.ivt[v].get(f,set())),scene_graph=g,source_image=str(self.image_path(v,f))))
return out
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