This project provides a complete pipeline for detecting agricultural pests using TensorFlow from scratch. It includes Jupyter notebooks for model training and inference, a custom pest dataset, and scripts to convert annotations into TFRecord format. The model uses a frozen TensorFlow object detection graph, and all outputs are saved locally after inference, making it suitable for offline or local use.
Pest Detection using Deep Learning
Pest Detection using Deep Learning
This project provides a complete pipeline for detecting agricultural pests using TensorFlow from scratch. It includes Jupyter notebooks for model training and inference, a custom pest dataset, and scripts to convert annotations into TFRecord format...
Organization
GitHub user
Deployment Model
Edge
Agricultural Production Step
Pest management
End User
Developers
Category
Used for
Crops
TRL
5-6
Community Engagement
High
Number of Forks
29
Country
Universal
Disclamer
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