Python util.predict_transform() Examples

The following are 7 code examples of util.predict_transform(). You can vote up the ones you like or vote down the ones you don't like, and go to the original project or source file by following the links above each example. You may also want to check out all available functions/classes of the module util , or try the search function .
Example #1
Source File: darknet.py    From SlowFast-Network-pytorch with MIT License 5 votes vote down vote up 
def forward(self, x, inp_dim, num_classes, confidence):
        x = x.data
        global CUDA
        prediction = x
        prediction = predict_transform(prediction, inp_dim, self.anchors, num_classes, confidence, CUDA)
        return prediction
Example #2
Source File: darknet.py    From pyCAIR with GNU General Public License v3.0 5 votes vote down vote up 
def forward(self, x, inp_dim, num_classes, confidence):
        x = x.data
        global CUDA
        prediction = x
        prediction = predict_transform(prediction, inp_dim, self.anchors, num_classes, confidence, CUDA)
        return prediction
Example #3
Source File: darknet.py    From semantic-object-accuracy-for-generative-text-to-image-synthesis with MIT License 5 votes vote down vote up 
def forward(self, x, inp_dim, num_classes, confidence):
        x = x.data
        global CUDA
        prediction = x
        prediction = predict_transform(prediction, inp_dim, self.anchors, num_classes, confidence, CUDA)
        return prediction
Example #4
Source File: darknet.py    From cvToolkit with MIT License 5 votes vote down vote up 
def forward(self, x, inp_dim, num_classes, confidence):
        x = x.data
        global CUDA
        prediction = x
        prediction = predict_transform(prediction, inp_dim, self.anchors, num_classes, confidence, CUDA)
        return prediction
Example #5
Source File: darknet.py    From hrnet with MIT License 5 votes vote down vote up 
def forward(self, x, inp_dim, num_classes, confidence):
        x = x.data
        global CUDA
        prediction = x
        prediction = predict_transform(prediction, inp_dim, self.anchors, num_classes, confidence, CUDA)
        return prediction
Example #6
Source File: darknet.py    From video-to-pose3D with MIT License 5 votes vote down vote up 
def forward(self, x, inp_dim, num_classes, confidence):
        x = x.data
        global CUDA
        prediction = x
        prediction = predict_transform(prediction, inp_dim, self.anchors, num_classes, confidence, CUDA)
        return prediction
Example #7
Source File: darknet.py    From video-to-pose3D with MIT License 5 votes vote down vote up 
def forward(self, x, inp_dim, num_classes, confidence):
        x = x.data
        global CUDA
        prediction = x
        prediction = predict_transform(prediction, inp_dim, self.anchors, num_classes, confidence, CUDA)
        return prediction