Poor performance 😞 after training on custom data ℹ️ about deep-text-recognition-benchmark HOT 1 OPEN

    if device == 'cpu':
        state_dict = torch.load(model_path, map_location=device)
        new_state_dict = OrderedDict()
        for key, value in state_dict.items():
            new_key = key[7:]
            new_state_dict[new_key] = value
        model.load_state_dict(new_state_dict)

        # Compare state_dict and new_state_dict
        differing_indices = []
        for idx, (key, state_value) in enumerate(state_dict.items()):
            new_value = new_state_dict.get(key, None)
            if new_value is not None and not torch.equal(state_value, new_value):
                differing_indices.append(idx)

        if len(differing_indices) == 0:
            print("The state_dict and new_state_dict are the same.")
        else:
            print("The state_dict and new_state_dict differ at the following indices:")
            print(differing_indices)

Output: The state_dict and new_state_dict are the same.