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A wrong weight file for demo codes #74

Description

@1511878618

I run this code with pretrained, the output is follow:

torchlm.runtime.bind(
    faceboxesv2(device="cpu")
)  # set device="cuda" if you want to run with CUDA
# set map_location="cuda" if you want to run with CUDA
torchlm.runtime.bind(
    pipnet(
        backbone="resnet18",
        pretrained=True,
        num_nb=10,
        num_lms=98,
        net_stride=32,
        input_size=256,
        meanface_type="wflw",
        map_location="cpu",
        # checkpoint="=pipnet_resnet18_10x98x32x256_wflw.pth",
    )
)  # will auto download pretrained weights from latest release if pretrained=True
# image should be HWC, BGR/RGB

landmarks, bboxes = torchlm.runtime.forward(
    image, swapRB_before_face=True, swapRB_before_landmarks=True
)
# swap h and w
# landmarks =
print(landmarks.shape)
image = torchlm.utils.draw_bboxes(image, bboxes=bboxes)
image = torchlm.utils.draw_landmarks(image, landmarks=landmarks)
Image.fromarray(image)

Image

If i downloaded the weights file from Releases with checkpoint, then it is ok

torchlm.runtime.bind(
    faceboxesv2(device="cpu")
)  # set device="cuda" if you want to run with CUDA
# set map_location="cuda" if you want to run with CUDA
torchlm.runtime.bind(
    pipnet(
        backbone="resnet18",
        pretrained=True,
        num_nb=10,
        num_lms=98,
        net_stride=32,
        input_size=256,
        meanface_type="wflw",
        map_location="cpu",
        checkpoint="=pipnet_resnet18_10x98x32x256_wflw.pth",
    )
)  # will auto download pretrained weights from latest release if pretrained=True
# image should be HWC, BGR/RGB

landmarks, bboxes = torchlm.runtime.forward(
    image, swapRB_before_face=True, swapRB_before_landmarks=True
)
# swap h and w
# landmarks =
print(landmarks.shape)
image = torchlm.utils.draw_bboxes(image, bboxes=bboxes)
image = torchlm.utils.draw_landmarks(image, landmarks=landmarks)
Image.fromarray(image)

Image

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