86 lines
3.2 KiB
Python
86 lines
3.2 KiB
Python
import os
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import argparse
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import glob
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import subprocess
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import onnxruntime
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from pathlib import Path
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from models.det_model.inference import PredictConfig, predict_image
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parser = argparse.ArgumentParser(description=__doc__)
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parser.add_argument("--infer_cfg", type=str, help="infer_cfg.yml",
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default="./models/det_model/model/infer_cfg.yml")
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parser.add_argument('--onnx_file', type=str, help="onnx model file path",
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default="./models/det_model/model/rtdetr_r50vd_6x_coco.onnx")
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parser.add_argument("--image_dir", type=str, default='./testImgs')
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parser.add_argument("--image_file", type=str)
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parser.add_argument("--imgsave_dir", type=str, default="./detect_results")
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parser.add_argument('--use_gpu', action='store_true', help='Whether to use GPU for inference', default=True)
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def get_test_images(infer_dir, infer_img):
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"""
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Get image path list in TEST mode
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"""
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assert infer_img is not None or infer_dir is not None, \
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"--image_file or --image_dir should be set"
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assert infer_img is None or os.path.isfile(infer_img), \
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"{} is not a file".format(infer_img)
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assert infer_dir is None or os.path.isdir(infer_dir), \
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"{} is not a directory".format(infer_dir)
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# infer_img has a higher priority
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if infer_img and os.path.isfile(infer_img):
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return [infer_img]
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images = set()
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infer_dir = os.path.abspath(infer_dir)
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assert os.path.isdir(infer_dir), \
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"infer_dir {} is not a directory".format(infer_dir)
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exts = ['jpg', 'jpeg', 'png', 'bmp']
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exts += [ext.upper() for ext in exts]
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for ext in exts:
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images.update(glob.glob('{}/*.{}'.format(infer_dir, ext)))
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images = list(images)
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assert len(images) > 0, "no image found in {}".format(infer_dir)
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print("Found {} inference images in total.".format(len(images)))
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return images
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def download_file(url, filename):
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print(f"Downloading {filename}...")
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subprocess.run(["wget", "-q", "--show-progress", "-O", filename, url], check=True)
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print("Download complete.")
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if __name__ == '__main__':
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cur_path = os.getcwd()
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script_dirpath = Path(__file__).resolve().parent
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os.chdir(script_dirpath)
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FLAGS = parser.parse_args()
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if not os.path.exists(FLAGS.infer_cfg):
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infer_cfg_url = "https://huggingface.co/TonyLee1256/texteller_det/resolve/main/infer_cfg.yml?download=true"
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download_file(infer_cfg_url, FLAGS.infer_cfg)
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if not os.path.exists(FLAGS.onnx_file):
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onnx_file_url = "https://huggingface.co/TonyLee1256/texteller_det/resolve/main/rtdetr_r50vd_6x_coco.onnx?download=true"
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download_file(onnx_file_url, FLAGS.onnx_file)
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# load image list
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img_list = get_test_images(FLAGS.image_dir, FLAGS.image_file)
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if FLAGS.use_gpu:
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predictor = onnxruntime.InferenceSession(FLAGS.onnx_file, providers=['CUDAExecutionProvider'])
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else:
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predictor = onnxruntime.InferenceSession(FLAGS.onnx_file, providers=['CPUExecutionProvider'])
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# load infer config
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infer_config = PredictConfig(FLAGS.infer_cfg)
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predict_image(FLAGS.imgsave_dir, infer_config, predictor, img_list)
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os.chdir(cur_path)
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