inference_general.yaml

Global:
  infer_imgs: "./drink_dataset_v2.0/test_images/100.jpeg"
  det_inference_model_dir: "./models/picodet_PPLCNet_x2_5_mainbody_lite_v1.0_infer"
  rec_inference_model_dir: "./models/general_PPLCNetV2_base_pretrained_v1.0_infer"
  rec_nms_thresold: 0.05

  batch_size: 1
  image_shape: [3, 640, 640]
  threshold: 0.2
  max_det_results: 5
  label_list:
    - foreground

  use_gpu: True
  enable_mkldnn: True
  cpu_num_threads: 10
  enable_benchmark: True
  use_fp16: False
  ir_optim: True
  use_tensorrt: False
  gpu_mem: 8000
  enable_profile: False

DetPreProcess:
  transform_ops:
    - DetResize:
        interp: 2
        keep_ratio: false
        target_size: [640, 640]
    - DetNormalizeImage:
        is_scale: true
        mean: [0.485, 0.456, 0.406]
        std: [0.229, 0.224, 0.225]
    - DetPermute: {}

DetPostProcess: {}

RecPreProcess:
  transform_ops:
    - ResizeImage:
        size: [224, 224]
        return_numpy: False
        interpolation: bilinear
        backend: cv2
    - NormalizeImage:
        scale: 1.0/255.0
        mean: [0.485, 0.456, 0.406]
        std: [0.229, 0.224, 0.225]
        order: hwc
    - ToCHWImage:

RecPostProcess: null

# indexing engine config
IndexProcess:
  index_method: "HNSW32" # supported: HNSW32, IVF, Flat
  image_root: "./drink_dataset_v2.0/gallery/"
  index_dir: "./drink_dataset_v2.0/index"
  data_file: "./drink_dataset_v2.0/gallery/drink_label.txt"
  index_operation: "new" # suported: "append", "remove", "new"
  delimiter: "\t"
  dist_type: "IP"
  embedding_size: 512
  batch_size: 32
  return_k: 5
  score_thres: 0.5