Merge pull request #10605 from PurdueDualityLab:yolov4_tiny_pr

PiperOrigin-RevId: 568323458

Author: tensorflower-gardener

official/projects/yolo/README.md

@@ -60,6 +60,7 @@ https://arxiv.org/abs/2103.14259)) which gives more gains on mAP.
 * Akhil Chinnakotla ([@GitHub The-Indian-Chinna](https://github.com/The-Indian-Chinna))
 * Tristan Yan ([@GitHub Tyan3001](https://github.com/Tyan3001))
 * Naveen Vivek ([@GitHub naveen-vivek](https://github.com/naveen-vivek))
+* Jacob Zietek ([@GitHub jacob-zietek](https://github.com/jacob-zietek))
 
 ### YOLOv7
 

official/projects/yolo/configs/experiments/yolov4/yolov4_tiny_416_tpu.yaml

@@ -0,0 +1,141 @@
+# --experiment_type=yolo_darknet
+# 21.21 AP
+# 41.68 AP50
+# 19.12 AP75
+# 29.59 APl
+# 23.94 APm
+# 9.67 APs
+
+runtime:
+  distribution_strategy: 'tpu'
+  mixed_precision_dtype: 'float32'
+task:
+  smart_bias_lr: 0.0
+  model:
+    darknet_based_model: true
+    input_size: [416, 416, 3]
+    backbone:
+      type: 'darknet'
+      darknet:
+        model_id: 'cspdarknettiny'
+        max_level: 5
+        min_level: 4
+    decoder:
+      type: yolo_decoder
+      yolo_decoder:
+        version: v4
+        type: tiny
+    head:
+      smart_bias: true
+    detection_generator:
+      box_type:
+        'all': original
+      scale_xy:
+        'all': 1.05
+      max_boxes: 300
+      nms_type: iou
+      iou_thresh: 0.001
+      nms_thresh: 0.60
+    loss:
+      use_scaled_loss: false
+      box_loss_type:
+        'all': ciou
+      ignore_thresh:
+        'all': 0.7
+      iou_normalizer:
+        'all': 0.07
+      cls_normalizer:
+        'all': 1.0
+      object_normalizer:
+        'all': 1.0
+      objectness_smooth:
+        'all': 0.0
+      max_delta:
+        'all': .inf
+    norm_activation:
+      activation: leaky
+      norm_epsilon: 0.00001
+      norm_momentum: 0.99
+      use_sync_bn: true
+    num_classes: 80
+    anchor_boxes:
+      anchors_per_scale: 3
+      boxes: [box: [10, 14], box: [23, 27], box: [37, 58], box: [81, 82], box: [135, 169], box: [344, 319]]
+  train_data:
+    prefetch_buffer_size: 32
+    global_batch_size: 512
+    dtype: float32
+    input_path: 'gs://cam2-datasets/coco/train*'
+    is_training: true
+    drop_remainder: true
+    seed: 1000
+    parser:
+      mosaic:
+        mosaic_frequency: 0.0
+        mixup_frequency: 0.0
+      max_num_instances: 300
+      letter_box: false
+      random_flip: true
+      aug_rand_saturation: 1.5
+      aug_rand_brightness: 1.5
+      aug_rand_hue: 0.1
+      aug_scale_min: 0.50
+      aug_scale_max: 1.5
+      aug_rand_translate: 0.0
+      jitter: 0.3
+      area_thresh: 0.0
+      random_pad: true
+      use_tie_breaker: false
+      best_match_only: false
+      anchor_thresh: 1.0
+  validation_data:
+    prefetch_buffer_size: 32
+    global_batch_size: 8
+    dtype: float32
+    input_path: 'gs://cam2-datasets/coco/val*'
+    is_training: false
+    drop_remainder: true
+    parser:
+      max_num_instances: 300
+      letter_box: false
+      use_tie_breaker: false
+      best_match_only: false
+      anchor_thresh: 1.0
+  weight_decay: 0.000
+  init_checkpoint: null
+  init_checkpoint_modules: null
+  annotation_file: null
+trainer:
+  best_checkpoint_eval_metric: 'AP'
+  best_checkpoint_export_subdir: 'best_ckpt'
+  best_checkpoint_metric_comp: 'higher'
+  train_steps: 553126
+  validation_steps: 625
+  steps_per_loop: 920
+  summary_interval: 920
+  validation_interval: 9200
+  checkpoint_interval: 920
+  optimizer_config:
+    ema:
+      average_decay: 0.9998
+      trainable_weights_only: false
+      dynamic_decay: true
+    learning_rate:
+      type: stepwise
+      stepwise:
+        boundaries: [442500, 497814]
+        name: PiecewiseConstantDecay
+        values: [0.04176, 0.004176, 0.0004176]
+    optimizer:
+      type: sgd_torch
+      sgd_torch:
+        momentum: 0.9
+        momentum_start: 0.9
+        nesterov: true
+        warmup_steps: 2000
+        weight_decay: 0.0005
+        name: SGD
+    warmup:
+      type: 'linear'
+      linear:
+        warmup_steps: 2000