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Pest Detection using Deep Learning and Tensorflow in python from scratch.

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KWOC slack channel link

https://join.slack.com/t/pestdetection/shared_invite/zt-jrnfw1md-KT7tyKC1xUC7W7t0Co7FZQ

Pest_detection

Pest Detection using Deep Learning and Tensorflow from scratch.

How to Run

Easy way: run pest_detection.ipynb Colab Notebook.

To retrain the weigth you can use pest_detection_weight.ipynb Colab Notebook.

Pest Dataset

Download Training Dataset from given Link

https://drive.google.com/file/d/1H1pf_NghWOKALC97_GpumriOSwt3xsTI/view?usp=sharing

Test Dataset is in Pest_val.zip

Inputs

  1. Convert the annotations and images from the train dataset into tfrecord.
  2. Upload labelmap.pbtx file in colab.

How to run inference on frozen TensorFlow graph

Requirements:

  1. frozen_inference_graph.pb Frozen TensorFlow object detection model downloaded from Colab after training.
  2. label_map.pbtxt File used to map correct name for predicted class index downloaded from Colab after training.

To perform predictions

  1. Put all the input image file in test/input/.
  2. Run pest_detection.ipynb Colab Notebook.
  3. All the outputs images will be stored in test/output/.

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Pest Detection using Deep Learning and Tensorflow in python from scratch.

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