forked from mindspore-Ecosystem/mindspore
fix fastrcnn eval failed
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@ -464,6 +464,15 @@ def create_fasterrcnn_dataset(mindrecord_file, batch_size=2, repeat_num=12, devi
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num_parallel_workers=num_parallel_workers)
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num_parallel_workers=num_parallel_workers)
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ds = ds.map(input_columns=["image", "image_shape", "box", "label", "valid_num"],
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ds = ds.map(input_columns=["image", "image_shape", "box", "label", "valid_num"],
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operations=flipped_generation, num_parallel_workers=4)
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operations=flipped_generation, num_parallel_workers=4)
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else:
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ds = ds.map(input_columns=["image", "annotation"],
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output_columns=["image", "image_shape", "box", "label", "valid_num"],
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columns_order=["image", "image_shape", "box", "label", "valid_num"],
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operations=compose_map_func,
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num_parallel_workers=num_parallel_workers)
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ds = ds.map(input_columns=["image"], operations=[normalize_op, type_cast0],
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num_parallel_workers=num_parallel_workers)
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# transpose_column from python to c
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# transpose_column from python to c
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ds = ds.map(input_columns=["image"], operations=[hwc_to_chw, type_cast1])
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ds = ds.map(input_columns=["image"], operations=[hwc_to_chw, type_cast1])
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@ -473,18 +482,5 @@ def create_fasterrcnn_dataset(mindrecord_file, batch_size=2, repeat_num=12, devi
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ds = ds.map(input_columns=["valid_num"], operations=[type_cast3])
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ds = ds.map(input_columns=["valid_num"], operations=[type_cast3])
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ds = ds.batch(batch_size, drop_remainder=True)
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ds = ds.batch(batch_size, drop_remainder=True)
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ds = ds.repeat(repeat_num)
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ds = ds.repeat(repeat_num)
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else:
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ds = ds.map(input_columns=["image", "annotation"],
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output_columns=["image", "image_shape", "box", "label", "valid_num"],
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columns_order=["image", "image_shape", "box", "label", "valid_num"],
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operations=compose_map_func,
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num_parallel_workers=num_parallel_workers)
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# transpose_column from python to c
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ds = ds.map(input_columns=["image"], operations=[hwc_to_chw, type_cast1])
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ds = ds.map(input_columns=["image_shape"], operations=[type_cast1])
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ds = ds.map(input_columns=["box"], operations=[type_cast1])
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ds = ds.map(input_columns=["label"], operations=[type_cast2])
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ds = ds.map(input_columns=["valid_num"], operations=[type_cast3])
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ds = ds.batch(batch_size, drop_remainder=True)
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ds = ds.repeat(repeat_num)
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return ds
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return ds
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