in source/d2_deserializer.py [0:0]
def json_to_d2(pred_dict, device):
"""
Client side helper function to deserialize the JSON msg back to d2 outputs
"""
# pred_dict = json.loads(predictions)
for k, v in pred_dict.items():
if k=="pred_boxes":
boxes_to_tensor = torch.FloatTensor(v).to(device)
pred_dict[k] = Boxes(boxes_to_tensor)
if k=="scores":
pred_dict[k] = torch.Tensor(v).to(device)
if k=="pred_classes":
pred_dict[k] = torch.Tensor(v).to(device).to(torch.uint8)
height, width = pred_dict['image_size']
del pred_dict['image_size']
inst = Instances((height, width,), **pred_dict)
return {'instances':inst}