106_object_detection_infer_plane
< 返回列表时间: 2020-03-19来源:OSCHINA
【围观】麒麟芯片遭打压成绝版,华为亿元投入又砸向了哪里?>>>
飞机目标检测 参考 源码notebook, https://github.com/databooks/databook/tree/master/gis/iobjectspy10 iObjects 10使用, 使用SuperMap iObjects for python 10.0 #!/usr/bin/env python3 # coding=utf-8 import os import time from iobjectspy.ml.vision import Inference Using TensorFlow backend.
设置输入数据路径 curr_dir = '' data_dir = os.path.join(curr_dir, '..','..','example_data') input_data = os.path.join(data_dir, 'inference/plane_infer.tif')
设置输出数据路径 out_dir = os.path.join(curr_dir, '..','..','out') out_data = os.path.join(curr_dir, '..','..','out','plane.udbx') if not os.path.exists(out_dir): os.makedirs(out_dir)
设置模型路径 model_path = os.path.join(curr_dir, '..','..','model','obj_det_plane','obj_det_plane.sdm')
目标检测类型 category_name = "plane"
基于影像文件进行飞机目标检测
影像文件格式支持 ‘tif’、‘img’(Erdas Image)、'jpg'、'png' 等,目标检测结果为GeoJSON文件,包含目标位置、类型等信息 目标检测类别支持 'plane', 'ship', 'tennis-court', 'vehicle' """ 影像文件格式支持 ‘tif’、‘img’(Erdas Image)、'jpg'、'png' 等 目标检测结果为GeoJSON文件,包含目标位置、类型等信息 """ start_time = time.time() result = Inference(input_data, model_path, out_data=out_data, out_dataset_name='out_plane').object_detect_infer( category_name, nms_thresh=0.3, score_thresh=0.3) end_time = time.time() print('耗时{}s'.format(end_time - start_time)) print('结果为{}'.format(result)) java -cp /home/data/hou/workspaces/iobjectspy/venv/lib/python3.6/site-packages/iobjectspy-10.0.0-py3.6.egg/iobjectspy/_jsuperpy/jars/iobjects-py4j.jar com.supermap.jsuperpy.ApplicationExample 127.0.0.1 51759 [iObjectsPy]: Connection gateway-service successful, Python callback port bind 40351 耗时8.400574445724487s 结果为out_plane_R
热门排行