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昇腾Pytorch镜像:https://ascendhub.huawei.com/#/detail/ascend-pytorch
代码仓:git clone https://gitee.com/ascend/modelzoo-GPL.git
coco测试验证集:wget https://bj-aicc.obs.cn-north-309.mtgascendic.cn/dataset/coco2017/coco.zip
coco训练集(放images下):wget https://bj-aicc.obs.cn-north-309.mtgascendic.cn/dataset/coco2017/train2017.zip
部分代码
# import StreamManagerApi.py from StreamManagerApi import * if __name__ == '__main__': # init stream manager streamManagerApi = StreamManagerApi() ret = streamManagerApi.InitManager() if ret != 0: print("Failed to init Stream manager, ret=%s" % str(ret)) exit() # create streams by pipeline config file with open("data/pipeline/Sample.pipeline", 'rb') as f: pipelineStr = f.read() ret = streamManagerApi.CreateMultipleStreams(pipelineStr) if ret != 0: print("Failed to create Stream, ret=%s" % str(ret)) exit() # Construct the input of the stream dataInput = MxDataInput() with open("data/test.jpg", 'rb') as f: dataInput.data = f.read() # The following is how to set the dataInput.roiBoxs """ roiVector = RoiBoxVector() roi = RoiBox() roi.x0 = 100 roi.y0 = 100 roi.x1 = 200 roi.y1 = 200 roiVector.push_back(roi) dataInput.roiBoxs = roiVector """ # Inputs data to a specified stream based on streamName. streamName = b'classification' inPluginId = 0 uniqueId = streamManagerApi.SendDataWithUniqueId(streamName, inPluginId, dataInput) if uniqueId < 0: print("Failed to send data to stream.") exit() # Obtain the inference result by specifying streamName and uniqueId. inferResult = streamManagerApi.GetResultWithUniqueId(streamName, uniqueId, 3000) if inferResult.errorCode != 0: print("GetResultWithUniqueId error. errorCode=%d, errorMsg=%s" % ( inferResult.errorCode, inferResult.data.decode())) exit() # print the infer result print(inferResult.data.decode()) # destroy streams streamManagerApi.DestroyAllStreams()
本来想一次性写完的,奈何装CANN的驱动装了一个礼拜,各种内核版本不匹配,国产AI硬件任重道远…
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