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configs/scrfd_2.5g.yaml

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+# SCRFD-2.5GF — Real-Time Model
+# WiderFace: 93.8/92.2/77.9 (Easy/Med/Hard) @ 400 FPS VGA on V100
+# Params: 0.67M | GFLOPs: 2.5
+
+model:
+  name: scrfd_2.5g
+  backbone:
+    stages: [2, 4, 4, 3]
+    widths: [24, 48, 96, 160]
+    block_type: basic
+  neck:
+    out_channels: 40
+    use_gn: true
+  head:
+    feat_channels: 40
+    stacked_convs: 2
+    num_anchors: 2
+    use_gn: true
+    use_landmarks: false
+  anchors:
+    strides: [8, 16, 32]
+    sizes: [[16, 32], [64, 128], [256, 512]]
+    ratios: [1.0]
+  matching:
+    type: atss
+    topk: 9
+  losses:
+    cls: gfl
+    reg: diou
+    cls_weight: 1.0
+    reg_weight: 2.0
+
+training:
+  epochs: 640
+  batch_size: 16     # Smaller model → can fit larger batch
+  optimizer:
+    type: sgd
+    lr: 0.02         # Scale with batch size
+    momentum: 0.9
+    weight_decay: 0.0005
+  lr_schedule:
+    warmup_epochs: 3
+    warmup_start_lr: 0.00001
+    type: multistep
+    milestones: [440, 544]
+    gamma: 0.1
+  amp: true
+  grad_clip: 35.0
+  pretrained: null
+
+data:
+  root: data/wider_face
+  input_size: 640
+  crop_scales: [0.3, 0.45, 0.6, 0.8, 1.0, 1.2, 1.4, 1.6, 1.8, 2.0]
+  mean: [104.0, 117.0, 123.0]
+  flip_prob: 0.5
+  min_face_size: 2
+  num_workers: 4
+  robustness_augmentation: true
+
+inference:
+  score_threshold: 0.3
+  nms_threshold: 0.4
+  max_detections: 750
+  input_size: 640