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https://github.com/PaddlePaddle/PaddleClas.git
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74 lines
1.7 KiB
YAML
74 lines
1.7 KiB
YAML
Global:
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infer_imgs: "./drink_dataset_v2.0/test_images/100.jpeg"
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det_inference_model_dir: "./models/picodet_PPLCNet_x2_5_mainbody_lite_v1.0_infer"
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rec_inference_model_dir: "./models/general_PPLCNetV2_base_pretrained_v1.0_infer"
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rec_nms_thresold: 0.05
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batch_size: 1
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image_shape: [3, 640, 640]
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threshold: 0.2
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max_det_results: 5
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label_list:
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- foreground
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use_gpu: True
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enable_mkldnn: True
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cpu_num_threads: 10
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enable_benchmark: True
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use_fp16: False
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ir_optim: True
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use_tensorrt: False
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gpu_mem: 8000
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enable_profile: False
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DetPreProcess:
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transform_ops:
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- DetResize:
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interp: 2
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keep_ratio: false
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target_size: [640, 640]
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- DetNormalizeImage:
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is_scale: true
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mean: [0.485, 0.456, 0.406]
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std: [0.229, 0.224, 0.225]
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- DetPermute: {}
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DetPostProcess: {}
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RecPreProcess:
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transform_ops:
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- ResizeImage:
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size: [224, 224]
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return_numpy: False
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interpolation: bilinear
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backend: cv2
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- NormalizeImage:
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scale: 1.0/255.0
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mean: [0.485, 0.456, 0.406]
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std: [0.229, 0.224, 0.225]
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order: hwc
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- ToCHWImage:
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RecPostProcess: null
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# evaluation config
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Eval:
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name: Vechicles
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image_root: ./Vechicles
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cls_label_path: ./Vechicles/query_list.txt
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output_dir: ./eval_output
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# indexing engine config
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IndexProcess:
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index_method: "HNSW32" # supported: HNSW32, IVF, Flat
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image_root: "./Vechicles/"
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index_dir: "./Vechicles/index"
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data_file: "./Vechicles/gallery_list.txt"
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index_operation: "new" # suported: "append", "remove", "new"
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delimiter: " "
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dist_type: "IP"
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embedding_size: 512
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batch_size: 32
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return_k: 5
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score_thres: 0.5
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