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README.md

NanoNets Object Detection Python Sample - Indian Roads Dataset

Golang Sample Python Sample Node.js Sample

Tracking Vehicles on Indian Roads

Vehicles on Indian Roads

Annotations are present for each frame and have the same name as the image name. You can find the example to train a model in python and node, by updating the api-key and model id in corresponding file. There is also a pre-processed json annotations folder that are ready payload for nanonets api.


Build an Object Detector for detecting Vehicles on Indian Roads

Note: Make sure you have python and pip installed on your system if you don't visit Python pip

Step 1: Clone the Repo

git clone https://github.com/NanoNets/object-detection-sample-python.git
cd object-detection-sample-python
sudo pip install requests

Step 2: Get your free API Key

Get your free API Key from http://app.nanonets.com/user/api_key

Step 3: Set the API key as an Environment Variable

export NANONETS_API_KEY=YOUR_API_KEY_GOES_HERE

Step 4: Create a New Model

python ./code/create-model.py

_Note: This generates a MODEL_ID that you need for the next step

Step 5: Add Model Id as Environment Variable

export NANONETS_MODEL_ID=YOUR_MODEL_ID

_Note: you will get YOUR_MODEL_ID from the previous step

Step 6: Upload the Training Data

The training data is found in images (image files) and annotations (annotations for the image files)

python ./code/upload-training.py

Step 7: Train Model

Once the Images have been uploaded, begin training the Model

python ./code/train-model.py

Step 8: Get Model State

The model takes ~2 hours to train. You will get an email once the model is trained. In the meanwhile you check the state of the model

python ./code/model-state.py

Step 9: Make Prediction

Once the model is trained. You can make predictions using the model

python ./code/prediction.py PATH_TO_YOUR_IMAGE.jpg

Sample Usage:

python ./code/prediction.py ./images/00O9CLJ7G4GKX1S.png

Note the python sample uses the comverted json instead of the xml payload for convenience purposes, hence it has no dependencies.