116 lines
3.4 KiB
Python
116 lines
3.4 KiB
Python
from __future__ import absolute_import
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from __future__ import division
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from __future__ import print_function
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import os
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import sys
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# add python path of PaddleDetection to sys.path
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parent_path = os.path.abspath(os.path.join(__file__, *(['..'] * 2)))
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sys.path.insert(0, parent_path)
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# ignore warning log
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import warnings
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warnings.filterwarnings('ignore')
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from ppdet.utils.cli import ArgsParser, merge_args
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from ppdet.core.workspace import load_config, merge_config
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from ppdet.utils.check import check_gpu, check_npu, check_xpu, check_version, check_config
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from ppdet.utils.cam_utils import BBoxCAM
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import paddle
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def parse_args():
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parser = ArgsParser()
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parser.add_argument(
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"--infer_img",
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type=str,
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default='demo/000000014439.jpg', # hxw: 404x640
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help="Image path, has higher priority over --infer_dir")
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parser.add_argument("--weights",
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type=str,
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default='output/faster_rcnn_r50_vd_fpn_2x_coco_paddlejob/best_model.pdparams'
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)
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parser.add_argument("--cam_out",
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type=str,
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default='cam_faster_rcnn'
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)
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parser.add_argument("--use_gpu",
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type=bool,
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default=True)
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parser.add_argument(
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"--infer_dir",
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type=str,
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default=None,
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help="Directory for images to perform inference on.")
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parser.add_argument(
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"--output_dir",
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type=str,
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default="output",
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help="Directory for storing the output visualization files.")
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parser.add_argument(
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"--draw_threshold",
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type=float,
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default=0.8,
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help="Threshold to reserve the result for visualization.")
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parser.add_argument(
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"--save_results",
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type=bool,
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default=False,
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help="Whether to save inference results to output_dir.")
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parser.add_argument(
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"--target_feature_layer_name",
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type=str,
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default='model.backbone', # define the featuremap to show grad cam, such as model.backbone, model.bbox_head.roi_extractor
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help="Whether to save inference results to output_dir.")
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args = parser.parse_args()
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return args
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def run(FLAGS, cfg):
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assert cfg.architecture in ['FasterRCNN', 'MaskRCNN', 'YOLOv3', 'PPYOLOE',
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'PPYOLOEWithAuxHead', 'BlazeFace', 'SSD', 'RetinaNet'], \
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'Only supported cam for faster_rcnn based and yolov3 based architecture for now, ' \
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'the others are not supported temporarily!'
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bbox_cam = BBoxCAM(FLAGS, cfg)
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bbox_cam.get_bboxes_cams()
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print('finish')
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def main():
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FLAGS = parse_args()
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cfg = load_config(FLAGS.config)
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merge_args(cfg, FLAGS)
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merge_config(FLAGS.opt)
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# disable npu in config by default
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if 'use_npu' not in cfg:
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cfg.use_npu = False
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# disable xpu in config by default
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if 'use_xpu' not in cfg:
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cfg.use_xpu = False
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if cfg.use_gpu:
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place = paddle.set_device('gpu')
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elif cfg.use_npu:
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place = paddle.set_device('npu')
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elif cfg.use_xpu:
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place = paddle.set_device('xpu')
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else:
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place = paddle.set_device('cpu')
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check_config(cfg)
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check_gpu(cfg.use_gpu)
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check_npu(cfg.use_npu)
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check_xpu(cfg.use_xpu)
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check_version()
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run(FLAGS, cfg)
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if __name__ == '__main__':
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main()
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