Upload projects/bdd100k.yml

projects/bdd100k.yml

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+# mean and std in RGB order, actually this part should remain unchanged as long as your dataset is similar to coco.
+mean: [0.485, 0.456, 0.406]
+std: [0.229, 0.224, 0.225]
+
+# this is coco anchors, change it if necessary
+#anchors_scales: '[2 ** 0, 2 ** 1/3, 2 ** 2/3]'
+#anchors_ratios: '[(0.7, 1.4), (1.0, 1.0), (1.4, 0.7)]'
+
+#anchors_scales: '[5.125, 0.625, 1.625]'
+#anchors_ratios: '[(1, 0.7317073170731707), (1, 0.85), (1, 0.7884615384615384)]'
+
+anchors_scales: '[2**0, 2**0.70, 2**1.32]'
+anchors_ratios: '[(0.62, 1.58), (1.0, 1.0), (1.58, 0.62)]'
+
+# must match your dataset's category_id.
+# category_id is one_indexed,
+# for example, index of 'car' here is 2, while category_id of is 3
+#obj_list: ['pedestrian',
+#          'rider',
+#          'car',
+#          'truck',
+#          'bus',
+#          'train',
+#          'motorcycle',
+#          'bicycle',
+#          'traffic light',
+#          'traffic sign']
+
+obj_list: ['car']
+
+seg_list: ['road',
+          'lane']
+
+dataset:
+  color_rgb: false
+  dataroot: ./datasets/bdd100k
+  labelroot: ./datasets/data2/zwt/bdd/bdd100k/labels/100k
+  laneroot: ./datasets/bdd_lane_gt
+  maskroot: ./datasets/bdd_seg_gt
+  data_format: jpg
+  flip: true
+  hsv_h: 0.015
+  hsv_s: 0.7
+  hsv_v: 0.4
+  org_img_size:
+  - 720
+  - 1280
+  rot_factor: 10
+  scale_factor: 0.25
+  shear: 0.0
+  test_set: val
+  train_set: train
+  translate: 0.1
+model:
+  image_size:
+  - 640
+  - 384
+need_autoanchor: false
+pin_memory: false
+num_seg_class: 2