Hi
I think the answers below have sufficient information.
I have to implement a Convolutional Neural Network, that takes a kinect image (1640480) and return a 1 x8 tensor predicting the class to which the object belongs and a 1 x 4 tensor, predicting the bounding box around the image, if its present.
Please help me how can I implement a suitable model to give two outputs and how to calculate loss and backpropagate in that case?
Also, i have just around 6000 training images, how can I achieve the best possible results with limited number of training i…
I have multiple losses, and i want to weight them seperately. More specifically, i want to set the weight of loss1 to 1, and the weight of loss2 to 0.5, is that correct?
loss1 = nn.L1Loss(B, A)
loss2 = nn.L1Loss(C, A)
loss2 = loss2*0.5
loss1.backward(retain_variables=True)
loss2.backward()
optimizer.step()
On the other hand, If Pytorch publishes more tutorials, especially non-vanilla learning models and mechanisms it will be beneficial in terms of practicality.