def _update(engine, batch):
x, indices = _prepare_batch(batch)
y_pred = model(x)
y_pred = F.softmax(y_pred, dim=1)
return {
"y_pred": convert_tensor(y_pred, device='cpu'),
"indices": indices
}
def __call__(self, img, faces):
if len(faces) == 0:
return []
# crop, face, target = self.transform((img, [face], img.size, target))
# return ((*crop, *face), target)
t = [self.transform((img, [f], img.size)) for f in faces]
# t = self.transform((img, faces, img.size))
t = [(*x[0], *x[1]) for x in t]
batch = default_collate(t)
batch = convert_tensor(batch, device='cuda')
preds = self.model(batch).data.cpu()
gaze_targets = [
cam2screen(p[0], p[1], self.device_params) for p in preds
]
return gaze_targets
def _prepare_batch(batch):
(x, y), indices = batch
x = convert_tensor(x, device=device)
return x, y, indices
