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Car Localization with Semantic Segmentation, using UNet. Dice Score: 0.89, Pixel to Pixel Accuracy: 99.07%.

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Name		Name	Last commit message	Last commit date
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Dataset		Dataset
results		results
LICENSE		LICENSE
README.md		README.md
config.py		config.py
dataset.py		dataset.py
model.py		model.py
train.py		train.py
utils.py		utils.py

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Car Localization with Semantic Segmentation using UNet

Training Dataset Source.
UNet PyTorch Tutorial.

Random Picks from Validation Dataset

Pixel to Pixel Accuracy: 99.07%
Dice Score: 0.89
Epochs: 100

Images:

Masks:

Predictions:

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Car Localization with Semantic Segmentation, using UNet. Dice Score: 0.89, Pixel to Pixel Accuracy: 99.07%.

python computer-vision deep-learning pytorch generative-adversarial-network convolutional-neural-networks image-segmentation unet unet-image-segmentation convnets

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