merge hrnet repo and simple baseline repo

anl13 · Dec 11, 2019 · 17c08ff · 17c08ff
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diff --git a/demo.sh b/demo.sh
@@ -1,3 +1,5 @@
 #!/bin/bash 
 
-python pose_estimation/demo.py --cfg experiments/pig/resnet152/384x288_d256x3_adam_lr1e-3.yaml 
+python pose_estimation/demo.py --cfg experiments/pig/resnet152/384x288_d256x3_adam_lr1e-3.yaml 
+
+# python pose_estimation/demo.py --cfg experiments/pig/w48_384x288-tiger.yaml
diff --git a/experiments/atrw/w48_384x288.yaml b/experiments/atrw/w48_384x288.yaml
@@ -0,0 +1,127 @@
+AUTO_RESUME: true
+CUDNN:
+  BENCHMARK: true
+  DETERMINISTIC: false
+  ENABLED: true
+DATA_DIR: ''
+GPUS: (0,)
+OUTPUT_DIR: 'output'
+LOG_DIR: 'log'
+WORKERS: 1
+PRINT_FREQ: 1
+
+DATASET:
+  COLOR_RGB: true
+  DATASET: 'atrw'
+  DATA_FORMAT: jpg
+  FLIP: true
+  NUM_JOINTS_HALF_BODY: 7
+  PROB_HALF_BODY: 0.5
+  ROOT: 'data/atrw/'
+  ROT_FACTOR: 45
+  SCALE_FACTOR: 0.35
+  TEST_SET: 'val'
+  TRAIN_SET: 'trainval'
+MODEL:
+  INIT_WEIGHTS: true
+  NAME: pose_hrnet
+  NUM_JOINTS: 15
+  PRETRAINED: 'models/pytorch/imagenet/hrnet_w32-36af842e.pth'
+  TARGET_TYPE: gaussian
+  IMAGE_SIZE:
+  - 384
+  - 288
+  HEATMAP_SIZE:
+  - 96
+  - 72
+  SIGMA: 3
+  EXTRA:
+    PRETRAINED_LAYERS:
+    - 'conv1'
+    - 'bn1'
+    - 'conv2'
+    - 'bn2'
+    - 'layer1'
+    - 'transition1'
+    - 'stage2'
+    - 'transition2'
+    - 'stage3'
+    - 'transition3'
+    - 'stage4'
+    FINAL_CONV_KERNEL: 1
+    STAGE2:
+      NUM_MODULES: 1
+      NUM_BRANCHES: 2
+      BLOCK: BASIC
+      NUM_BLOCKS:
+      - 4
+      - 4
+      NUM_CHANNELS:
+      - 32
+      - 64
+      FUSE_METHOD: SUM
+    STAGE3:
+      NUM_MODULES: 4
+      NUM_BRANCHES: 3
+      BLOCK: BASIC
+      NUM_BLOCKS:
+      - 4
+      - 4
+      - 4
+      NUM_CHANNELS:
+      - 32
+      - 64
+      - 128
+      FUSE_METHOD: SUM
+    STAGE4:
+      NUM_MODULES: 3
+      NUM_BRANCHES: 4
+      BLOCK: BASIC
+      NUM_BLOCKS:
+      - 4
+      - 4
+      - 4
+      - 4
+      NUM_CHANNELS:
+      - 32
+      - 64
+      - 128
+      - 256
+      FUSE_METHOD: SUM
+LOSS:
+  USE_TARGET_WEIGHT: true
+TRAIN:
+  BATCH_SIZE_PER_GPU: 8
+  SHUFFLE: true
+  BEGIN_EPOCH: 0
+  END_EPOCH: 120
+  OPTIMIZER: adam
+  LR: 0.0005
+  LR_FACTOR: 0.1
+  LR_STEP:
+  - 90
+  - 110
+  WD: 0.0001
+  GAMMA1: 0.99
+  GAMMA2: 0.0
+  MOMENTUM: 0.9
+  NESTEROV: false
+TEST:
+  BATCH_SIZE_PER_GPU: 8
+  COCO_BBOX_FILE: ''
+  BBOX_THRE: 1.0
+  IMAGE_THRE: 0.0
+  IN_VIS_THRE: 0.2
+  MODEL_FILE: 'output/atrw/pose_hrnet/w48_384x288/model_best.pth'
+  NMS_THRE: 1.0
+  OKS_THRE: 0.9
+  USE_GT_BBOX: true
+  FLIP_TEST: true
+  POST_PROCESS: true
+  SHIFT_HEATMAP: true
+DEBUG:
+  DEBUG: true
+  SAVE_BATCH_IMAGES_GT: true
+  SAVE_BATCH_IMAGES_PRED: true
+  SAVE_HEATMAPS_GT: true
+  SAVE_HEATMAPS_PRED: true
diff --git a/experiments/coco/hrnet/w32_256x192_adam_lr1e-3.yaml b/experiments/coco/hrnet/w32_256x192_adam_lr1e-3.yaml
@@ -0,0 +1,127 @@
+AUTO_RESUME: true
+CUDNN:
+  BENCHMARK: true
+  DETERMINISTIC: false
+  ENABLED: true
+DATA_DIR: ''
+GPUS: (0,1,2,3)
+OUTPUT_DIR: 'output'
+LOG_DIR: 'log'
+WORKERS: 24
+PRINT_FREQ: 100
+
+DATASET:
+  COLOR_RGB: true
+  DATASET: 'coco'
+  DATA_FORMAT: jpg
+  FLIP: true
+  NUM_JOINTS_HALF_BODY: 8
+  PROB_HALF_BODY: 0.3
+  ROOT: 'data/coco/'
+  ROT_FACTOR: 45
+  SCALE_FACTOR: 0.35
+  TEST_SET: 'val2017'
+  TRAIN_SET: 'train2017'
+MODEL:
+  INIT_WEIGHTS: true
+  NAME: pose_hrnet
+  NUM_JOINTS: 17
+  PRETRAINED: 'models/pytorch/imagenet/hrnet_w32-36af842e.pth'
+  TARGET_TYPE: gaussian
+  IMAGE_SIZE:
+  - 192
+  - 256
+  HEATMAP_SIZE:
+  - 48
+  - 64
+  SIGMA: 2
+  EXTRA:
+    PRETRAINED_LAYERS:
+    - 'conv1'
+    - 'bn1'
+    - 'conv2'
+    - 'bn2'
+    - 'layer1'
+    - 'transition1'
+    - 'stage2'
+    - 'transition2'
+    - 'stage3'
+    - 'transition3'
+    - 'stage4'
+    FINAL_CONV_KERNEL: 1
+    STAGE2:
+      NUM_MODULES: 1
+      NUM_BRANCHES: 2
+      BLOCK: BASIC
+      NUM_BLOCKS:
+      - 4
+      - 4
+      NUM_CHANNELS:
+      - 32
+      - 64
+      FUSE_METHOD: SUM
+    STAGE3:
+      NUM_MODULES: 4
+      NUM_BRANCHES: 3
+      BLOCK: BASIC
+      NUM_BLOCKS:
+      - 4
+      - 4
+      - 4
+      NUM_CHANNELS:
+      - 32
+      - 64
+      - 128
+      FUSE_METHOD: SUM
+    STAGE4:
+      NUM_MODULES: 3
+      NUM_BRANCHES: 4
+      BLOCK: BASIC
+      NUM_BLOCKS:
+      - 4
+      - 4
+      - 4
+      - 4
+      NUM_CHANNELS:
+      - 32
+      - 64
+      - 128
+      - 256
+      FUSE_METHOD: SUM
+LOSS:
+  USE_TARGET_WEIGHT: true
+TRAIN:
+  BATCH_SIZE_PER_GPU: 32
+  SHUFFLE: true
+  BEGIN_EPOCH: 0
+  END_EPOCH: 210
+  OPTIMIZER: adam
+  LR: 0.001
+  LR_FACTOR: 0.1
+  LR_STEP:
+  - 170
+  - 200
+  WD: 0.0001
+  GAMMA1: 0.99
+  GAMMA2: 0.0
+  MOMENTUM: 0.9
+  NESTEROV: false
+TEST:
+  BATCH_SIZE_PER_GPU: 32
+  COCO_BBOX_FILE: 'data/coco/person_detection_results/COCO_val2017_detections_AP_H_56_person.json'
+  BBOX_THRE: 1.0
+  IMAGE_THRE: 0.0
+  IN_VIS_THRE: 0.2
+  MODEL_FILE: ''
+  NMS_THRE: 1.0
+  OKS_THRE: 0.9
+  USE_GT_BBOX: true
+  FLIP_TEST: true
+  POST_PROCESS: true
+  SHIFT_HEATMAP: true
+DEBUG:
+  DEBUG: true
+  SAVE_BATCH_IMAGES_GT: true
+  SAVE_BATCH_IMAGES_PRED: true
+  SAVE_HEATMAPS_GT: true
+  SAVE_HEATMAPS_PRED: true
diff --git a/experiments/coco/hrnet/w32_384x288_adam_lr1e-3.yaml b/experiments/coco/hrnet/w32_384x288_adam_lr1e-3.yaml
@@ -0,0 +1,127 @@
+AUTO_RESUME: true
+CUDNN:
+  BENCHMARK: true
+  DETERMINISTIC: false
+  ENABLED: true
+DATA_DIR: ''
+GPUS: (0,1,2,3)
+OUTPUT_DIR: 'output'
+LOG_DIR: 'log'
+WORKERS: 24
+PRINT_FREQ: 100
+
+DATASET:
+  COLOR_RGB: true
+  DATASET: 'coco'
+  DATA_FORMAT: jpg
+  FLIP: true
+  NUM_JOINTS_HALF_BODY: 8
+  PROB_HALF_BODY: 0.3
+  ROOT: 'data/coco/'
+  ROT_FACTOR: 45
+  SCALE_FACTOR: 0.35
+  TEST_SET: 'val2017'
+  TRAIN_SET: 'train2017'
+MODEL:
+  INIT_WEIGHTS: true
+  NAME: pose_hrnet
+  NUM_JOINTS: 17
+  PRETRAINED: 'models/pytorch/imagenet/hrnet_w32-36af842e.pth'
+  TARGET_TYPE: gaussian
+  IMAGE_SIZE:
+  - 288
+  - 384
+  HEATMAP_SIZE:
+  - 72
+  - 96
+  SIGMA: 3
+  EXTRA:
+    PRETRAINED_LAYERS:
+    - 'conv1'
+    - 'bn1'
+    - 'conv2'
+    - 'bn2'
+    - 'layer1'
+    - 'transition1'
+    - 'stage2'
+    - 'transition2'
+    - 'stage3'
+    - 'transition3'
+    - 'stage4'
+    FINAL_CONV_KERNEL: 1
+    STAGE2:
+      NUM_MODULES: 1
+      NUM_BRANCHES: 2
+      BLOCK: BASIC
+      NUM_BLOCKS:
+      - 4
+      - 4
+      NUM_CHANNELS:
+      - 32
+      - 64
+      FUSE_METHOD: SUM
+    STAGE3:
+      NUM_MODULES: 4
+      NUM_BRANCHES: 3
+      BLOCK: BASIC
+      NUM_BLOCKS:
+      - 4
+      - 4
+      - 4
+      NUM_CHANNELS:
+      - 32
+      - 64
+      - 128
+      FUSE_METHOD: SUM
+    STAGE4:
+      NUM_MODULES: 3
+      NUM_BRANCHES: 4
+      BLOCK: BASIC
+      NUM_BLOCKS:
+      - 4
+      - 4
+      - 4
+      - 4
+      NUM_CHANNELS:
+      - 32
+      - 64
+      - 128
+      - 256
+      FUSE_METHOD: SUM
+LOSS:
+  USE_TARGET_WEIGHT: true
+TRAIN:
+  BATCH_SIZE_PER_GPU: 32
+  SHUFFLE: true
+  BEGIN_EPOCH: 0
+  END_EPOCH: 210
+  OPTIMIZER: adam
+  LR: 0.001
+  LR_FACTOR: 0.1
+  LR_STEP:
+  - 170
+  - 200
+  WD: 0.0001
+  GAMMA1: 0.99
+  GAMMA2: 0.0
+  MOMENTUM: 0.9
+  NESTEROV: false
+TEST:
+  BATCH_SIZE_PER_GPU: 32
+  COCO_BBOX_FILE: 'data/coco/person_detection_results/COCO_val2017_detections_AP_H_56_person.json'
+  BBOX_THRE: 1.0
+  IMAGE_THRE: 0.0
+  IN_VIS_THRE: 0.2
+  MODEL_FILE: ''
+  NMS_THRE: 1.0
+  OKS_THRE: 0.9
+  USE_GT_BBOX: true
+  FLIP_TEST: true
+  POST_PROCESS: true
+  SHIFT_HEATMAP: true
+DEBUG:
+  DEBUG: true
+  SAVE_BATCH_IMAGES_GT: true
+  SAVE_BATCH_IMAGES_PRED: true
+  SAVE_HEATMAPS_GT: true
+  SAVE_HEATMAPS_PRED: true