add reid config

ppcls/configs/Pedestrian/reid_sb_ResNet50.yaml

+# global configs
+Global:
+  checkpoints: null
+  pretrained_model: null
+  output_dir: "./output/"
+  device: "gpu"
+  save_interval: 1
+  eval_during_train: True
+  eval_interval: 1
+  epochs: 120
+  print_batch_step: 10
+  use_visualdl: False
+  # used for static mode and model export
+  image_shape: [3, 256, 128]
+  save_inference_dir: "./inference"
+  eval_mode: "retrieval"
+
+# model architecture
+Arch:
+  name: "RecModel"
+  infer_output_key: "features"
+  infer_add_softmax: False
+  Backbone:
+    name: "ResNet50"
+    pretrained: True
+  BackboneStopLayer:
+    name: "avg_pool"
+  Head:
+    name: "FC"
+    embedding_size: 2048
+    class_num: 1501
+
+# loss function config for traing/eval process
+Loss:
+  Train:
+    - CELoss:
+        weight: 1.0
+    - TripletLoss:
+        weight: 1.0
+  Eval:
+    - CELoss:
+        weight: 1.0
+
+Optimizer:
+  name: Adam
+  lr:
+    name: Piecewise
+    boundaries: 30, 60
+    values: 0.00035, 0.000035, 0.0000035
+    warmup_epoch: 10
+    warmup_start_lr: 0.0000035
+  regularizer:
+    name: 'L2'
+    coeff: 0.0005
+
+# data loader for train and eval
+DataLoader:
+  Train:
+    dataset:
+        name: "VeriWild"
+        image_root: "./dataset/VeRI-Wild/images/"
+        cls_label_path: "./dataset/VeRI-Wild/train_test_split/train_list_start0.txt"
+        transform_ops:
+          - DecodeImage:
+              to_rgb: True
+              channel_first: False
+          - ResizeImage:
+              size: (256, 128)
+          - RandFlipImage:
+              flip_code: 1
+          - Pad: 10
+          - RandCropImage:
+              size: （256， 128）
+          - NormalizeImage:
+              scale: 0.00392157
+              mean: [0.485, 0.456, 0.406]
+              std: [0.229, 0.224, 0.225]
+              order: ''
+          - RandomErasing:
+              EPSILON: 0.5
+              sl: 0.02
+              sh: 0.4
+              r1: 0.3
+              mean: [0.4914, 0.4822, 0.4465]
+    sampler:
+        name: PKSampler
+        batch_size: 128
+        sample_per_id: 4
+        drop_last: True
+        shuffle: True
+    loader:
+        num_workers: 6
+        use_shared_memory: True
+  Eval:
+    Query:
+      dataset:
+        name: "VeriWild"
+        image_root: "./dataset/VeRI-Wild/images"
+        cls_label_path: "./dataset/VeRI-Wild/train_test_split/test_3000_id_query.txt"
+        transform_ops:
+          - DecodeImage:
+              to_rgb: True
+              channel_first: False
+          - ResizeImage:
+              size: (256, 128)
+          - NormalizeImage:
+              scale: 0.00392157
+              mean: [0.485, 0.456, 0.406]
+              std: [0.229, 0.224, 0.225]
+              order: ''
+      sampler:
+        name: DistributedBatchSampler
+        batch_size: 64
+        drop_last: False
+        shuffle: False
+      loader:
+        num_workers: 6
+        use_shared_memory: True
+
+    Gallery:
+      dataset:
+        name: "VeriWild"
+        image_root: "./dataset/VeRI-Wild/images"
+        cls_label_path: "./dataset/VeRI-Wild/train_test_split/test_3000_id.txt"
+        transform_ops:
+          - DecodeImage:
+              to_rgb: True
+              channel_first: False
+          - ResizeImage:
+              size: (256, 128)
+          - NormalizeImage:
+              scale: 0.00392157
+              mean: [0.485, 0.456, 0.406]
+              std: [0.229, 0.224, 0.225]
+              order: ''
+      sampler:
+        name: DistributedBatchSampler
+        batch_size: 64
+        drop_last: False
+        shuffle: False
+      loader:
+        num_workers: 6
+        use_shared_memory: True
+
+Metric:
+  Eval:
+    - Recallk:
+        topk: [1, 5]
+    - mAP: {}
+

ppcls/data/preprocess/__init__.py

@@ -29,6 +29,7 @@ from ppcls.data.preprocess.ops.operators import RandFlipImage
 from ppcls.data.preprocess.ops.operators import NormalizeImage
 from ppcls.data.preprocess.ops.operators import ToCHWImage
 from ppcls.data.preprocess.ops.operators import AugMix
+from ppcls.data.preprocess.ops.operators import Pad
 
 from ppcls.data.preprocess.batch_ops.batch_operators import MixupOperator, CutmixOperator, OpSampler, FmixOperator
 

ppcls/data/preprocess/ops/operators.py

@@ -25,6 +25,7 @@ import cv2
 import numpy as np
 from PIL import Image
 from paddle.vision.transforms import ColorJitter as RawColorJitter
+from paddle.vision.transforms import Pad
 
 from .autoaugment import ImageNetPolicy
 from .functional import augmentations