Merged commit includes the following changes: (#8830)

320622111  by rathodv:

    Internal Change.

--

PiperOrigin-RevId: 320622111

Co-authored-by: TF Object Detection Team <[email protected]>

Author: tombstone

research/object_detection/README.md

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+# CenterNet meta-architecture from the "Objects as Points" [2] paper with the
+# hourglass[1] backbone.
+# [1]: https://arxiv.org/abs/1603.06937
+# [2]: https://arxiv.org/abs/1904.07850
+# Trained on COCO, initialized from Extremenet Detection checkpoint
+# Train on TPU-32 v3
+#
+# Achieves 44.6 mAP on COCO17 Val
+
+
+model {
+  center_net {
+    num_classes: 90
+    feature_extractor {
+      type: "hourglass_104"
+      bgr_ordering: true
+      channel_means: [104.01362025, 114.03422265, 119.9165958 ]
+      channel_stds: [73.6027665 , 69.89082075, 70.9150767 ]
+    }
+    image_resizer {
+      keep_aspect_ratio_resizer {
+        min_dimension: 1024
+        max_dimension: 1024
+        pad_to_max_dimension: true
+      }
+    }
+    object_detection_task {
+      task_loss_weight: 1.0
+      offset_loss_weight: 1.0
+      scale_loss_weight: 0.1
+      localization_loss {
+        l1_localization_loss {
+        }
+      }
+    }
+    object_center_params {
+      object_center_loss_weight: 1.0
+      min_box_overlap_iou: 0.7
+      max_box_predictions: 100
+      classification_loss {
+        penalty_reduced_logistic_focal_loss {
+          alpha: 2.0
+          beta: 4.0
+        }
+      }
+    }
+  }
+}
+
+train_config: {
+
+  batch_size: 128
+  num_steps: 50000
+
+  data_augmentation_options {
+    random_horizontal_flip {
+    }
+  }
+
+  data_augmentation_options {
+    random_adjust_hue {
+    }
+  }
+
+  data_augmentation_options {
+    random_adjust_contrast {
+    }
+  }
+
+  data_augmentation_options {
+    random_adjust_saturation {
+    }
+  }
+
+  data_augmentation_options {
+    random_adjust_brightness {
+    }
+  }
+
+   data_augmentation_options {
+     random_square_crop_by_scale {
+      scale_min: 0.6
+      scale_max: 1.3
+    }
+  }
+
+  optimizer {
+    adam_optimizer: {
+      epsilon: 1e-7  # Match tf.keras.optimizers.Adam's default.
+      learning_rate: {
+        cosine_decay_learning_rate {
+          learning_rate_base: 1e-3
+          total_steps: 50000
+          warmup_learning_rate: 2.5e-4
+          warmup_steps: 5000
+        }
+      }
+    }
+    use_moving_average: false
+  }
+  max_number_of_boxes: 100
+  unpad_groundtruth_tensors: false
+
+  fine_tune_checkpoint_version: V2
+  fine_tune_checkpoint: "PATH_TO_BE_CONFIGURED/ckpt-1"
+  fine_tune_checkpoint_type: "detection"
+}
+
+train_input_reader: {
+  label_map_path: "PATH_TO_BE_CONFIGURED/label_map.txt"
+  tf_record_input_reader {
+    input_path: "PATH_TO_BE_CONFIGURED/train2017-?????-of-00256.tfrecord"
+  }
+}
+
+eval_config: {
+  metrics_set: "coco_detection_metrics"
+  use_moving_averages: false
+  batch_size: 1;
+}
+
+eval_input_reader: {
+  label_map_path: "PATH_TO_BE_CONFIGURED/label_map.txt"
+  shuffle: false
+  num_epochs: 1
+  tf_record_input_reader {
+    input_path: "PATH_TO_BE_CONFIGURED/val2017-?????-of-00032.tfrecord"
+  }
+}

research/object_detection/configs/tf2/center_net_hourglass104_1024x1024_coco17_tpu-32.config

@@ -0,0 +1,143 @@
+# CenterNet meta-architecture from the "Objects as Points" [2] paper with the
+# hourglass[1] backbone.
+# [1]: https://arxiv.org/abs/1603.06937
+# [2]: https://arxiv.org/abs/1904.07850
+# Trained on COCO, initialized from Extremenet Detection checkpoint
+# Train on TPU-8
+#
+# Achieves 41.9 mAP on COCO17 Val
+
+model {
+  center_net {
+    num_classes: 90
+    feature_extractor {
+      type: "hourglass_104"
+      bgr_ordering: true
+      channel_means: [104.01362025, 114.03422265, 119.9165958 ]
+      channel_stds: [73.6027665 , 69.89082075, 70.9150767 ]
+    }
+    image_resizer {
+      keep_aspect_ratio_resizer {
+        min_dimension: 512
+        max_dimension: 512
+        pad_to_max_dimension: true
+      }
+    }
+    object_detection_task {
+      task_loss_weight: 1.0
+      offset_loss_weight: 1.0
+      scale_loss_weight: 0.1
+      localization_loss {
+        l1_localization_loss {
+        }
+      }
+    }
+    object_center_params {
+      object_center_loss_weight: 1.0
+      min_box_overlap_iou: 0.7
+      max_box_predictions: 100
+      classification_loss {
+        penalty_reduced_logistic_focal_loss {
+          alpha: 2.0
+          beta: 4.0
+        }
+      }
+    }
+  }
+}
+
+train_config: {
+
+  batch_size: 128
+  num_steps: 140000
+
+  data_augmentation_options {
+    random_horizontal_flip {
+    }
+  }
+
+  data_augmentation_options {
+    random_crop_image {
+      min_aspect_ratio: 0.5
+      max_aspect_ratio: 1.7
+      random_coef: 0.25
+    }
+  }
+
+
+  data_augmentation_options {
+    random_adjust_hue {
+    }
+  }
+
+  data_augmentation_options {
+    random_adjust_contrast {
+    }
+  }
+
+  data_augmentation_options {
+    random_adjust_saturation {
+    }
+  }
+
+  data_augmentation_options {
+    random_adjust_brightness {
+    }
+  }
+
+  data_augmentation_options {
+    random_absolute_pad_image {
+       max_height_padding: 200
+       max_width_padding: 200
+       pad_color: [0, 0, 0]
+    }
+  }
+
+  optimizer {
+    adam_optimizer: {
+      epsilon: 1e-7  # Match tf.keras.optimizers.Adam's default.
+      learning_rate: {
+        manual_step_learning_rate {
+          initial_learning_rate: 1e-3
+          schedule {
+           step: 90000
+           learning_rate: 1e-4
+          }
+          schedule {
+            step: 120000
+            learning_rate: 1e-5
+          }
+        }
+      }
+    }
+    use_moving_average: false
+  }
+  max_number_of_boxes: 100
+  unpad_groundtruth_tensors: false
+
+  fine_tune_checkpoint_version: V2
+  fine_tune_checkpoint: "PATH_TO_BE_CONFIGURED/ckpt-1"
+  fine_tune_checkpoint_type: "detection"
+}
+
+train_input_reader: {
+  label_map_path: "PATH_TO_BE_CONFIGURED/label_map.txt"
+  tf_record_input_reader {
+    input_path: "PATH_TO_BE_CONFIGURED/train2017-?????-of-00256.tfrecord"
+  }
+}
+
+eval_config: {
+  metrics_set: "coco_detection_metrics"
+  use_moving_averages: false
+  batch_size: 1;
+}
+
+eval_input_reader: {
+  label_map_path: "PATH_TO_BE_CONFIGURED/label_map.txt"
+  shuffle: false
+  num_epochs: 1
+  tf_record_input_reader {
+    input_path: "PATH_TO_BE_CONFIGURED/val2017-?????-of-00032.tfrecord"
+  }
+}