PPYOLOE Python部署

import fastdeploy as fd

model_url = "https://bj.bcebos.com/paddlehub/fastdeploy/ppyoloe_crn_l_300e_coco.tgz"
image_url = "https://bj.bcebos.com/fastdeploy/tests/test_det.jpg"
fd.download_and_decompress(model_url, path=".")
fd.download(image_url, path=".")

model_file = "ppyoloe_crn_l_300e_coco/model.pdmodel"
params_file = "ppyoloe_crn_l_300e_coco/model.pdiparams"
infer_cfg_file = "ppyoloe_crn_l_300e_coco/infer_cfg.yml"

# 模型推理的配置信息
option = fd.RuntimeOption()
model = fd.vision.detection.PPYOLOE(model_file, params_file, infer_cfg_file, option)

[INFO] fastdeploy/fastdeploy_runtime.cc(283)::Init	Runtime initialized with Backend::OPENVINO in device Device::CPU.

import cv2
im = cv2.imread("test_det.jpg")

result = model.predict(im)
print(result)

DetectionResult: [xmin, ymin, xmax, ymax, score, label_id]
415.047180,89.311569, 506.009613, 283.863098, 0.950423, 0
163.665710,81.914932, 198.585342, 166.760895, 0.896433, 0
581.788635,113.027618, 612.623474, 198.521713, 0.842596, 0
267.217224,89.777306, 298.796051, 169.361526, 0.837951, 0
104.465584,45.482422, 127.688850, 93.533867, 0.773348, 0
...
...

vis_im = fd.vision.visualize.vis_detection(im, result, score_threshold=0.5)
cv2.imwrite("vis_image.jpg", vis_im)