Delete Base-DensePose-RCNN-FPN.yaml

Base-DensePose-RCNN-FPN.yaml

@@ -1,60 +0,0 @@
-VERSION: 2
-MODEL:
-  META_ARCHITECTURE: "GeneralizedRCNN"
-  BACKBONE:
-    NAME: "build_resnet_fpn_backbone"
-  RESNETS:
-    OUT_FEATURES: ["res2", "res3", "res4", "res5"]
-  FPN:
-    IN_FEATURES: ["res2", "res3", "res4", "res5"]
-  ANCHOR_GENERATOR:
-    SIZES: [[32], [64], [128], [256], [512]]  # One size for each in feature map
-    ASPECT_RATIOS: [[0.5, 1.0, 2.0]]  # Three aspect ratios (same for all in feature maps)
-  RPN:
-    IN_FEATURES: ["p2", "p3", "p4", "p5", "p6"]
-    PRE_NMS_TOPK_TRAIN: 2000  # Per FPN level
-    PRE_NMS_TOPK_TEST: 1000  # Per FPN level
-    # Detectron1 uses 2000 proposals per-batch,
-    # (See "modeling/rpn/rpn_outputs.py" for details of this legacy issue)
-    # which is approximately 1000 proposals per-image since the default batch size for FPN is 2.
-    POST_NMS_TOPK_TRAIN: 1000
-    POST_NMS_TOPK_TEST: 1000
-
-  DENSEPOSE_ON: True
-  ROI_HEADS:
-    NAME: "DensePoseROIHeads"
-    IN_FEATURES: ["p2", "p3", "p4", "p5"]
-    NUM_CLASSES: 1
-  ROI_BOX_HEAD:
-    NAME: "FastRCNNConvFCHead"
-    NUM_FC: 2
-    POOLER_RESOLUTION: 7
-    POOLER_SAMPLING_RATIO: 2
-    POOLER_TYPE: "ROIAlign"
-  ROI_DENSEPOSE_HEAD:
-    NAME: "DensePoseV1ConvXHead"
-    POOLER_TYPE: "ROIAlign"
-    NUM_COARSE_SEGM_CHANNELS: 2
-    PREDICTOR_NAME: "DensePoseEmbeddingPredictor"
-    LOSS_NAME: "DensePoseCseLoss"
-    CSE:
-      # embedding loss, possible values:
-      # - "EmbeddingLoss"
-      # - "SoftEmbeddingLoss"
-      EMBED_LOSS_NAME: "EmbeddingLoss"
-SOLVER:
-  IMS_PER_BATCH: 16
-  BASE_LR: 0.01
-  STEPS: (60000, 80000)
-  MAX_ITER: 90000
-  WARMUP_FACTOR: 0.1
-  CLIP_GRADIENTS:
-    CLIP_TYPE: norm
-    CLIP_VALUE: 1.0
-    ENABLED: true
-    NORM_TYPE: 2.0
-INPUT:
-  MIN_SIZE_TRAIN: (640, 672, 704, 736, 768, 800)
-DENSEPOSE_EVALUATION:
-  TYPE: cse
-  STORAGE: file