eval_dcam_adb_tri.py

import os
import cv2
import numpy as np
import  torch
import dcam_model as model
p1='./Test_set/trimapsA/'
p2='./Test_set/mergedA/'
p3a='./DCAMOUT/'
p1='O:/DATAS/Combined_Dataset/Test_set/trimapsA/'

p2='O:/DATAS/Combined_Dataset/Test_set/mergedA/'
p3a='g:/dcamadb/'
os.makedirs(p3a,exist_ok=True)

if __name__ == '__main__':
    segmodel = model.DCAM_ADB_TRI()
    segmodel.load_state_dict(torch.load('./dcam_adb_tri.ckpt',map_location='cpu')['model'])
    segmodel=segmodel.cuda()
    segmodel.eval()
    for idx,file in enumerate(os.listdir(p1)) :
        print(idx)
        rawimg=p2+file
        trimap=p1+file
        rawimg=cv2.imread(rawimg)
        trimap=cv2.imread(trimap,cv2.IMREAD_GRAYSCALE)
        trimap_nonp=trimap.copy()
        h,w,c=rawimg.shape
        nonph,nonpw,_=rawimg.shape
        newh= (((h-1)//32)+1)*32
        neww= (((w-1)//32)+1)*32
        padh=newh-h
        padh1=int(padh/2)
        padh2=padh-padh1
        padw=neww-w
        padw1=int(padw/2)
        padw2=padw-padw1
        rawimg_pad=cv2.copyMakeBorder(rawimg,padh1,padh2,padw1,padw2,cv2.BORDER_REFLECT)
        trimap_pad=cv2.copyMakeBorder(trimap,padh1,padh2,padw1,padw2,cv2.BORDER_REFLECT)
        h_pad,w_pad,_=rawimg_pad.shape
        tritemp = np.zeros([*trimap_pad.shape, 3], np.float32)
        tritemp[:, :, 0] = (trimap_pad == 0)
        tritemp[:, :, 1] = (trimap_pad == 128)
        tritemp[:, :, 2] = (trimap_pad == 255)
        tritemp2=np.transpose(tritemp,(2,0,1))
        tritemp2=tritemp2[np.newaxis,:,:,:]
        img=np.transpose(rawimg_pad,(2,0,1))[np.newaxis,::-1,:,:]
        img=np.array(img,np.float32)
        img=img/255.
        img=torch.from_numpy(img).cuda()
        tritemp2=torch.from_numpy(tritemp2).cuda()
        with torch.no_grad():
            _,_,_,pred=segmodel(img,tritemp2)
            pred=pred.detach().cpu().numpy()[0]
            pred=pred[:,padh1:padh1+h,padw1:padw1+w]
            preda=pred[0:1,]*255
            preda=np.transpose(preda,(1,2,0))
            preda=preda*(trimap_nonp[:,:,None]==128)+(trimap_nonp[:,:,None]==255)*255
        preda=np.array(preda,np.uint8)
        cv2.imwrite(p3a+file,preda)