bash create_custom_model.sh 2(我的数据集是2类-car/plane) 然后将yolov3-custom.cfg中的anchor换成我们得到的anchor 之后运行 python3 train.py --model_def config/yolov3-custom.cfg --data_config config/custom.data 1. 2. 3. 4. 5. 三、测试 3.1 测试map python3 test.py --model_def config...
depth_multiple: 0.33 # model depth multiple 控制模型的深度 width_multiple: 0.50 # layer channel multiple 控制conv 通道的个数,卷积核数量 #depth_multiple: 表示BottleneckCSP模块的层缩放因子,将所有的BotleneckCSP模块的B0ttleneck乘上该参数得到最终个数 #width_multiple表示卷积通道的缩放因子,就是将配置里...
2. OpenVINO在CPU下支持模型格式是FP32,NCS设备上支持的格式是FP16 python3 mo_caffe.py --input_proto yolo v3-tiny.prototxt --input_model yolo v3-tiny.caffemodel --data_type FP16 --output_dir FP16 --model_name yolo v3-tiny --scale_value data[255.0] 至此完成模型的准备工作,还差最后一步。
device=torch_utils.select_device(opt.device)# Initialize model model=Darknet(opt.cfg,img_size)# Load weightsattempt_download(weights)ifweights.endswith('.pt'):# pytorch format model.load_state_dict(torch.load(weights,map_location=device)['model'])else:# darknet formatload_darknet_weights(mod...
# model settingsmodel = dict( type='YOLOV3', pretrained='open-mmlab://darknet53', backbone=dict( type='Darknet', depth=53, out_indices=(3, 4, 5) ), neck=dict( type='YOLOV3Neck', num_scales=3, in_channels=[1024, 512, 256], out_channels=[512, 256, 128]), bbox_head=dict...
策略源自Lam1360/YOLOv3-model-pruning(https://github.com/Lam1360/YOLOv3-model-pruning),这是一种保守的策略,因为yolov3中有五组共23处shortcut连接,对应的是add操作,通道剪枝后如何保证shortcut的两个输入维度一致,这是必须考虑的问题。而La...
bash create_custom_model.sh 2(我的数据集是2类-car/plane) 然后将yolov3-custom.cfg中的anchor换成我们得到的anchor 之后运行 python3 train.py --model_def config/yolov3-custom.cfg --data_config config/custom.data 三、测试 3.1 测试map
Build the TensorRT engine from the pre-trained googlenet (ILSVRC2012) model. Note that I downloaded the pre-trained model files fromBVLC caffeand have put a copy of all necessary files in this repository. $cd${HOME}/project/tensorrt_demos/googlenet$make$./create_engine ...
Model: YOLOv3 Transforms: - Resize: interp: CUBIC target_size: 608 - Normalize: mean: - 0.485 - 0.456 - 0.406 std: - 0.229 - 0.224 - 0.225 TransformsMode: RGB _Attributes: eval_metrics: bbox_map: 60.483796531022485 fixed_input_shape: null labels: - head - helmet - person model_type:...
Run the getModels.sh filefromcommand line to download the needed model files sudo chmod a+x getModels.sh ./getModels.sh Python: Commandline usage to colorize a single image: python3 object_detection_yolo.py--image=bird.jpg a video file: ...