Create README.md
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README.md
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---
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license: apache-2.0
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metrics:
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- accuracy
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- f1
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---
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Returns treffic sign given an image.
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See https://www.kaggle.com/code/dima806/traffic-sign-detection-vit for more details.
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```
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Classification report:
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precision recall f1-score support
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Bicycles crossing 1.0000 0.9423 0.9703 52
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Children crossing 0.6711 1.0000 0.8031 51
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Danger Ahead 0.8254 1.0000 0.9043 52
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Dangerous curve to the left 0.8400 0.4118 0.5526 51
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Dangerous curve to the right 0.5636 0.6078 0.5849 51
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Dont Go Left 0.8909 0.9608 0.9245 51
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Dont Go Left or Right 0.6145 1.0000 0.7612 51
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Dont Go Right 0.8367 0.7885 0.8119 52
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Dont Go straight 1.0000 0.8235 0.9032 51
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Dont Go straight or left 0.8611 0.5962 0.7045 52
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Dont overtake from Left 0.9545 0.8235 0.8842 51
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Fences 0.9808 1.0000 0.9903 51
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Go Left 0.7931 0.8846 0.8364 52
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Go Left or right 0.8000 0.4615 0.5854 52
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Go Right 0.8197 0.9804 0.8929 51
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Go left or straight 0.8571 0.4706 0.6076 51
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Go right or straight 0.5714 0.1569 0.2462 51
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Go straight 1.0000 0.2745 0.4308 51
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Go straight or right 0.8696 0.7692 0.8163 52
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Heavy Vehicle Accidents 0.9583 0.9020 0.9293 51
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Horn 0.9444 1.0000 0.9714 51
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No Car 0.9808 1.0000 0.9903 51
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No Uturn 0.9057 0.9412 0.9231 51
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No entry 0.6892 1.0000 0.8160 51
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No horn 0.9455 1.0000 0.9720 52
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No stopping 1.0000 1.0000 1.0000 51
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Road Divider 1.0000 0.7115 0.8315 52
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Roundabout mandatory 0.9811 1.0000 0.9905 52
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Speed limit (15km/h) 0.9756 0.7843 0.8696 51
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Speed limit (30km/h) 0.6901 0.9423 0.7967 52
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Speed limit (40km/h) 0.6818 0.5882 0.6316 51
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Speed limit (50km/h) 0.8919 0.6471 0.7500 51
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Speed limit (5km/h) 0.8772 0.9804 0.9259 51
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Speed limit (60km/h) 1.0000 0.1731 0.2951 52
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Speed limit (70km/h) 0.8197 0.9615 0.8850 52
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Train Crossing 0.8361 1.0000 0.9107 51
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Under Construction 0.9778 0.8462 0.9072 52
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Unknown 0.7917 0.3725 0.5067 51
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Uturn 0.9630 1.0000 0.9811 52
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Zebra Crossing 0.8077 0.8077 0.8077 52
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ZigZag Curve 0.3542 1.0000 0.5231 51
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keep Left 0.5312 0.6538 0.5862 52
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keep Right 0.7400 0.7115 0.7255 52
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speed limit (80km/h) 0.5385 0.9608 0.6901 51
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watch out for cars 0.9804 0.9804 0.9804 51
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accuracy 0.7981 2313
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macro avg 0.8358 0.7981 0.7868 2313
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weighted avg 0.8360 0.7981 0.7869 2313
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```
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