mmdeploy/demo/python/object_detection.py

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# Copyright (c) OpenMMLab. All rights reserved.
import argparse
import cv2
[Refactor] Rename mmdeploy_python to mmdeploy_runtime (#1911) * [Feature]: Add github prebuild workflow after new release. (#1852) * add prebuild dockerfile * add prebuild test workflw * update * update * rm other workflow for test * Update docker image * add win1o prebuild * add test prebuild * add windows scripts in prebuilt package * add linux scripts in prebuilt package * generate_build_config.py * fix cudnn search * fix env * fix script * fix rpath * fix cwd * fix windows * fix lint * windows prebuild ci * linux prebuild ci * fix * update trigger * Revert "rm other workflow for test" This reverts commit 0a0387275014efab71046d33a0e52904672b4012. * update sdk build readme * update prebuild * fix dll deps for python >= 3.8 on windows * fix ci * test prebuild * update test script to avoid modify upload folder * add onnxruntime.dll to mmdeploy_python * update prebuild workflow * update prebuild * Update loader.cpp.in * remove exists prebuild files * fix opencv env * update cmake options for mmdeploy python build * remove test code * fix lint --------- Co-authored-by: RunningLeon <mnsheng@yeah.net> Co-authored-by: RunningLeon <maningsheng@sensetime.com> * rename mmdeploy_python -> mmdeploy_runtime * test master prebuild * fix trt net build * Revert "test master prebuild" This reverts commit aad5258648f5f2c410c965b295c309fd1166da22. * add master branch * fix linux set_env script * update package_tools docs * fix gcc 7.3 aligned_alloc * comment temporarily as text_det_recog can't be built with prebuild package built under manylinux --------- Co-authored-by: RunningLeon <mnsheng@yeah.net> Co-authored-by: RunningLeon <maningsheng@sensetime.com>
2023-03-29 19:02:37 +08:00
from mmdeploy_runtime import Detector
def parse_args():
parser = argparse.ArgumentParser(
description='show how to use sdk python api')
parser.add_argument('device_name', help='name of device, cuda or cpu')
parser.add_argument(
'model_path',
help='path of mmdeploy SDK model dumped by model converter')
parser.add_argument('image_path', help='path of an image')
args = parser.parse_args()
return args
def main():
args = parse_args()
img = cv2.imread(args.image_path)
detector = Detector(
model_path=args.model_path, device_name=args.device_name, device_id=0)
bboxes, labels, masks = detector(img)
indices = [i for i in range(len(bboxes))]
for index, bbox, label_id in zip(indices, bboxes, labels):
[left, top, right, bottom], score = bbox[0:4].astype(int), bbox[4]
if score < 0.3:
continue
cv2.rectangle(img, (left, top), (right, bottom), (0, 255, 0))
if masks[index].size:
mask = masks[index]
blue, green, red = cv2.split(img)
mask_img = blue[top:top + mask.shape[0], left:left + mask.shape[1]]
cv2.bitwise_or(mask, mask_img, mask_img)
img = cv2.merge([blue, green, red])
cv2.imwrite('output_detection.png', img)
if __name__ == '__main__':
main()