import sys,os,glob,pickle,numpy as np,cv2,json
sys.path.insert(0,'code'); sys.path.insert(0,os.path.dirname(__file__))
os.environ['YOLO_OFFLINE']='1'
from detector import ShelfProductDetector
from variants import Matcher
from PIL import Image
det=ShelfProductDetector()
res={}
for cat in sys.argv[1:]:
    name=os.path.basename(cat); m=Matcher(cat,root=True,geom='affine',scales=(200,400)); rows=[]
    for p in sorted(glob.glob('add/*')):
        if 'image6' in p: continue
        im=cv2.cvtColor(np.array(Image.open(p).convert('RGB')),cv2.COLOR_RGB2BGR)
        for b in det.detect(im).get('boxes',[]):
            x1,y1,x2,y2=[int(v) for v in b['box']]; c=im[max(0,y1):y2,max(0,x1):x2]
            if c.size==0 or min(c.shape[:2])<20: continue
            rows.append(dict(img=p,ev=m.score(c)))
    res[name]=rows; print(name,len(rows),'distractor crops')
pickle.dump(res,open(f'{os.path.dirname(__file__)}/distract.pkl','wb'))