Running this evaluation code, yields very weird results. I understand that I only have 69 images in faces directory but aren’t these results very weird?
# Test the model
model.eval() # eval mode (batchnorm uses moving mean/variance instead of mini-batch mean/variance)
with torch.no_grad():
correct = 0
total = 0
for i, sample_batched in enumerate(train_loader):
print(i, sample_batched['image'].size(),
sample_batched['landmarks'].size())
images_batch, landmarks_batch = \
sample_batched['image'], sample_batched['landmarks']
images = images_batch
labels = landmarks_batch.reshape(-1, 68 * 2)
images = Variable(images.float())
labels = Variable(labels)
images = images.to(device)
labels = labels.to(device)
outputs = model(images)
#_, predicted = torch.max(outputs.data, 1)
#_, predicted = outputs.data
print("Predicted", outputs.data.shape)
outputs = outputs.cpu()
images = images.cpu()
if i_batch == 3:
plt.figure()
show_landmarks_batch({'image': images, 'landmarks': outputs.data.reshape(-1, 68, 2) })
plt.axis('off')
plt.ioff()
plt.show()
show_landmarks_batch({'image': images, 'landmarks': labels.reshape(-1, 68, 2) })
plt.axis('off')
plt.ioff()
plt.show()
break
(base) mona@mona:~/research/facial_landmark$ ls faces/*.jpg | wc -l
69
I also have to mention I have a very terrible test loss:
size of train loader is: 1
type(loss_train_step) is: <class 'torch.Tensor'>
loss_train_step.dtype is: torch.float32
Test Steps: 1/1 Loss: 15511.6732
--------------------------------------------------
Epoch: 1 Train Loss: 15590.3896 Test Loss: 15511.6732
--------------------------------------------------
Minimum Test Loss of 15511.6732 at epoch 1/10
Model Saved
size of train loader is: 1
type(loss_train_step) is: <class 'torch.Tensor'>
loss_train_step.dtype is: torch.float32
Test Steps: 1/1 Loss: 16363.6969
--------------------------------------------------
Epoch: 2 Train Loss: 15584.9707 Test Loss: 16363.6969
--------------------------------------------------
size of train loader is: 1
type(loss_train_step) is: <class 'torch.Tensor'>
loss_train_step.dtype is: torch.float32
Test Steps: 1/1 Loss: 16458.4072
--------------------------------------------------
Epoch: 3 Train Loss: 15594.6885 Test Loss: 16458.4072
--------------------------------------------------
size of train loader is: 1
type(loss_train_step) is: <class 'torch.Tensor'>
loss_train_step.dtype is: torch.float32
Test Steps: 1/1 Loss: 15063.5689
--------------------------------------------------
Epoch: 4 Train Loss: 16293.1094 Test Loss: 15063.5689
--------------------------------------------------
Minimum Test Loss of 15063.5689 at epoch 4/10
Model Saved
size of train loader is: 1
type(loss_train_step) is: <class 'torch.Tensor'>
loss_train_step.dtype is: torch.float32
Test Steps: 1/1 Loss: 16673.0292
--------------------------------------------------
Epoch: 5 Train Loss: 14949.3047 Test Loss: 16673.0292
--------------------------------------------------
size of train loader is: 1
type(loss_train_step) is: <class 'torch.Tensor'>
loss_train_step.dtype is: torch.float32
Test Steps: 1/1 Loss: 15699.0407
--------------------------------------------------
Epoch: 6 Train Loss: 16076.5234 Test Loss: 15699.0407
--------------------------------------------------
size of train loader is: 1
type(loss_train_step) is: <class 'torch.Tensor'>
loss_train_step.dtype is: torch.float32
Test Steps: 1/1 Loss: 15512.4619
--------------------------------------------------
Epoch: 7 Train Loss: 15775.4736 Test Loss: 15512.4619
--------------------------------------------------
size of train loader is: 1
type(loss_train_step) is: <class 'torch.Tensor'>
loss_train_step.dtype is: torch.float32
Test Steps: 1/1 Loss: 16625.0978
--------------------------------------------------
Epoch: 8 Train Loss: 14958.9971 Test Loss: 16625.0978
--------------------------------------------------
size of train loader is: 1
type(loss_train_step) is: <class 'torch.Tensor'>
loss_train_step.dtype is: torch.float32
Test Steps: 1/1 Loss: 15330.6030
--------------------------------------------------
Epoch: 9 Train Loss: 15395.0596 Test Loss: 15330.6030
--------------------------------------------------
size of train loader is: 1
type(loss_train_step) is: <class 'torch.Tensor'>
loss_train_step.dtype is: torch.float32
Test Steps: 1/1 Loss: 15949.3246
--------------------------------------------------
Epoch: 10 Train Loss: 15716.1689 Test Loss: 15949.3246
--------------------------------------------------
Training Complete
Total Elapsed Time : 19.73250699043274 s
This is how the evaluation results look in the original file here: Google Colab
