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+# Object Detection Model based on TensorFlow 1 Detection Model Zoo
+
+[![TensorFlow 1.15](https://img.shields.io/badge/TensorFlow-1.15-FF6F00?logo=tensorflow)](https://github.com/tensorflow/tensorflow/releases/tag/v1.15.0)
+[![Python 3.6](https://img.shields.io/badge/Python-3.6-3776AB)](https://www.python.org/downloads/release/python-360/)
+
+![obj-detector-setup](../imgs/Rad_Fig_v4_ObjDet.png)
+
+## Setup
+
+Detectors are implemented with Tensorflow 1.15 and trained on NVIDIA GeForce RTX/GTX GPU devices with CUDA version 9 or 10.
+
+Object detection model is trained with Tensorflow [Object Detection API](https://github.com/tensorflow/models/blob/master/research/object_detection/g3doc/tf1.md). Faster R-CNN with Resnet101 is selected from the Tensorflow Object Detection [Model Zoo](https://github.com/tensorflow/models/blob/master/research/object_detection/g3doc/tf1_detection_zoo.md). The Faster R-CNN with Resnet101 backbone ([faster_rcnn_resnet101_coco](http://download.tensorflow.org/models/object_detection/faster_rcnn_resnet101_coco_2018_01_28.tar.gz)) is pre-trained on the [COCO dataset](http://cocodataset.org), and is used to initialize our object detector model.
+
+
+## Configuring Spine ROI Detection Model
+
+Our spinal regions of interest (ROI) detection models are trained with the following customizations:
+- graph protos (`*.pbtxt`) for either axial (left, center or right) or sagittal
+- config files (`*.config`) to generate the model graphs
+  - change the following
+    - num_classes
+    - batch_size
+    - fine_tune_checkpoint
+    - train_input_reader path
+    - eval_input_reader path
+
+### Train the Object Detection Model and Export Inference Graph
+
+You can follow the guides and tutorials in the "References" below on TF1 object detection. Please make sure you are using a compatible commit of TF1 object detection repo.
+
+We have provided two bash scripts to launch the training and exportation of trained graph:
+- init training `obj_det_train_py.sh`
+- export inference graph `obj_det_export_inference.sh`
+
+### Inspect Object Detection with Pickle
+
+`Object-Detection/object_detection.py` is used to generate the detection pickle file.
+
+## References
+- TF1 Object Detection API https://github.com/tensorflow/models/blob/master/research/object_detection/g3doc/tf1.md
+- TF1 Detection Model Zoo https://github.com/tensorflow/models/blob/master/research/object_detection/g3doc/tf1_detection_zoo.md
+- TF1 Faster R-CNN with Resnet101 pre-trained on COCO dataset http://download.tensorflow.org/models/object_detection/faster_rcnn_resnet101_coco_2018_01_28.tar.gz
+- Tutorial on TF1 object detection: https://pythonprogramming.net/introduction-use-tensorflow-object-detection-api-tutorial/