Add at new repo again

vton-api/preprocess/humanparsing/mhp_extension/detectron2/configs/Cityscapes/mask_rcnn_R_50_FPN.yaml

@@ -0,0 +1,27 @@
+_BASE_: "../Base-RCNN-FPN.yaml"
+MODEL:
+  # WEIGHTS: "detectron2://ImageNetPretrained/MSRA/R-50.pkl"
+  # For better, more stable performance initialize from COCO
+  WEIGHTS: "detectron2://COCO-InstanceSegmentation/mask_rcnn_R_50_FPN_3x/137849600/model_final_f10217.pkl"
+  MASK_ON: True
+  ROI_HEADS:
+    NUM_CLASSES: 8
+# This is similar to the setting used in Mask R-CNN paper, Appendix A
+# But there are some differences, e.g., we did not initialize the output
+# layer using the corresponding classes from COCO
+INPUT:
+  MIN_SIZE_TRAIN: (800, 832, 864, 896, 928, 960, 992, 1024)
+  MIN_SIZE_TRAIN_SAMPLING: "choice"
+  MIN_SIZE_TEST: 1024
+  MAX_SIZE_TRAIN: 2048
+  MAX_SIZE_TEST: 2048
+DATASETS:
+  TRAIN: ("cityscapes_fine_instance_seg_train",)
+  TEST: ("cityscapes_fine_instance_seg_val",)
+SOLVER:
+  BASE_LR: 0.01
+  STEPS: (18000,)
+  MAX_ITER: 24000
+  IMS_PER_BATCH: 8
+TEST:
+  EVAL_PERIOD: 8000