Pre-trained weight on the unipose_mpii predictions looks bad

[mukeshnarendran7]

Have loaded the pre-trained weights and made some predictions with the unipose modeland the predictions looks off

criterion   = torch.nn.MSELoss()
optimizer   = torch.optim.Adam(model.parameters(), lr=1e-3)
model = unipose(dataset="MPII",backbone='resnet', output_stride=16)

#load weights of the model

model.load_state_dict(torch.load("/content/UniPose_MPII.pth",map_location='cpu'))
model.eval()

trfm = transforms.Compose(
                          [
                          transforms.ToTensor()                                      
                          ]
                          )
DEVICE     = "cuda" if torch.cuda.is_available() else "cpu"
img = cv2.resize(cv2.imread("/content/fed.jpg"), (513, 513))
img2 = trfm(img)[None].to(DEVICE, dtype=torch.float)

model.eval()
hmp = model(img2)

[lhwlqh]

can you give me the pre trained weight?