Method __call__

bench/python/nvcodec_utils.py:532–569

(self)

        # docs_tag: end_init_imagebatchdecoder_nvimagecodec

    def __call__(self):
        if self.total_decoded == len(self.file_names):
            return None

        # docs_tag: begin_call_imagebatchdecoder_nvimagecodec
        self.cvcuda_perf.push_range("decoder.nvimagecodec")

        file_name_batch = self.file_name_batches[self.batch_idx]

        data_batch = [open(path, "rb").read() for path in file_name_batch]

        # docs_tag: begin_decode_imagebatchdecoder_nvimagecodec

        tensor_list = []
        image_list = self.decoder.decode(data_batch, cuda_stream=self.cuda_stream)

        # Convert the decoded images to cvcuda tensors in a list.
        for i in range(len(image_list)):
            tensor_list.append(cvcuda.as_tensor(image_list[i], "HWC"))

        # Stack the list of tensors to a single NHWC tensor.
        cvcuda_decoded_tensor = cvcuda.stack(tensor_list)
        self.total_decoded += len(tensor_list)
        # docs_tag: end_decode_imagebatchdecoder_nvimagecodec

        # docs_tag: begin_return_imagebatchdecoder_nvimagecodec
        batch = Batch(
            batch_idx=self.batch_idx,
            data=cvcuda_decoded_tensor,
            fileinfo=file_name_batch,
        )
        self.batch_idx += 1

        # docs_tag: end_return_imagebatchdecoder_nvimagecodec

        self.cvcuda_perf.pop_range()
        # docs_tag: end_call_imagebatchdecoder_nvimagecodec
        return batch

    def start(self):
        pass