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@@ -58,7 +58,9 @@ Create a folder directly in C: and name it “tensorflow1”. This working direc
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Download the full TensorFlow object detection repository located at https://github.com/tensorflow/models by clicking the “Clone or Download” button and downloading the zip file. Open the downloaded zip file and extract the “models-master” folder directly into the C:\tensorflow1 directory you just created. Rename “models-master” to just “models”.
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Note: The TensorFlow models repository's code (which contains the object detection API) is continuously updated by the developers. Sometimes they make changes that break functionality with old versions of TensorFlow. It is always best to use the latest version of TensorFlow and download the latest models repository. This tutorial was done using TensorFlow v1.5 and this [GitHub commit](https://github.com/tensorflow/models/tree/079d67d9a0b3407e8d074a200780f3835413ef99) of the TensorFlow Object Detection API. If portions of this tutorial do not work, it may be necessary to install TensorFlow v1.5 and use this exact commit rather than the most up-to-date version.
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(Note: The TensorFlow models repository's code (which contains the object detection API) is continuously updated by the developers. Sometimes they make changes that break functionality with old versions of TensorFlow. It is always best to use the latest version of TensorFlow and download the latest models repository.
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This tutorial was originally done using TensorFlow v1.5 and this [GitHub commit](https://github.com/tensorflow/models/tree/079d67d9a0b3407e8d074a200780f3835413ef99) of the TensorFlow Object Detection API. If portions of this tutorial do not work, it may be necessary to install TensorFlow v1.5 and use this exact commit rather than the most up-to-date version.)
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#### 2b. Download the Faster-RCNN-Inception-V2-COCO model from TensorFlow's model zoo
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TensorFlow provides several object detection models (pre-trained classifiers with specific neural network architectures) in its [model zoo](https://github.com/tensorflow/models/blob/master/research/object_detection/g3doc/detection_model_zoo.md). Some models (such as the SSD-MobileNet model) have an architecture that allows for faster detection but with less accuracy, while some models (such as the Faster-RCNN model) give slower detection but with more accuracy. I initially started with the SSD-MobileNet-V1 model, but it didn’t do a very good job identifying the cards in my images. I re-trained my detector on the Faster-RCNN-Inception-V2 model, and the detection worked considerably better, but with a noticeably slower speed.

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