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Object Detection Example

This example uses tensorflow object detection model API and TensorFlowSharp library to identify multiple objects in a single image using .NET programming languages like C# and F#.

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Run example

  1. git clone https://github.com/migueldeicaza/TensorFlowSharp
  2. build TensorFlowSharp.sln
  3. copy 'libtensorflow.dylib' (Mac OS) or 'libtensorflow.dll' (Windows) to the project output path (see where you can get the library under Working on TensorFlowSharp section)
  4. Run the ExampleObjectDetection util from command line:
ExampleObjectDetection

By default, the example downloads a pretrained model, but you can specify your own using the following options:

input_image - optional, the path to the image for processing (the default is 'test_images/input.jpg')
output_image - optional, the path where the image with detected objects will be saved (the default is 'test_images/output.jpg')
catalog - optional, the path to the '.pbtxt' file (by default, 'mscoco_label_map.pbtxt' been loaded)
model - optional, the path to the '.pb' file (by default, 'frozen_inference_graph.pb' model been used, but you can download any other from here https://github.com/tensorflow/models/blob/master/research/object_detection/g3doc/detection_model_zoo.md or train your own):

ExampleObjectDetection --input_image="/demo/input.jpg" --output_image="/demo/output.jpg" --catalog="/demo/mscoco_label_map.pbtxt" --model="/demo/frozen_inference_graph.pb"

I found an issue in the example

If you want to address a bug or a question related to the object detection example - just create a new issue on github starting with [Object Detection Example] tag.