GitHub - MetaDev/TrafficSignRecognition: Machine learning project to classify traffic sign images. Previously hosted on university Github account.

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Machine learning project to classify traffic sign images. Previously hosted on university Github account.

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Name		Name	Last commit message	Last commit date
Latest commit History 168 Commits
__pycache__		__pycache__
csv		csv
images		images
old		old
report		report
sandbox		sandbox
.gitignore		.gitignore
.spyderproject		.spyderproject
.~lock.ultimate2.csv#		.~lock.ultimate2.csv#
ForestReportTest.py		ForestReportTest.py
Group10_Deadline1.zip		Group10_Deadline1.zip
Jumparound.py		Jumparound.py
README.txt		README.txt
__init__.py		__init__.py
automatic_rotation.py		automatic_rotation.py
best_models.py		best_models.py
best_models_covnet.py		best_models_covnet.py
best_models_featureless_covnet.py		best_models_featureless_covnet.py
best_models_overnight_run.py		best_models_overnight_run.py
convnet.py		convnet.py
csv_output.py		csv_output.py
daisy.csv		daisy.csv
data.txt		data.txt
data_loading.py		data_loading.py
distance_model.py		distance_model.py
distance_model_testing.py		distance_model_testing.py
env.bat		env.bat
feature_extraction.py		feature_extraction.py
feature_validation.py		feature_validation.py
frequencydomain_kfold_cross_validation.py		frequencydomain_kfold_cross_validation.py
fun_testing.py		fun_testing.py
fun_testing_pieter.py		fun_testing_pieter.py
grouped_kfold.py		grouped_kfold.py
image_operations.py		image_operations.py
image_transformation_testing.py		image_transformation_testing.py
image_transformation_testing_freq.py		image_transformation_testing_freq.py
image_transformation_testing_pieter.py		image_transformation_testing_pieter.py
machine-learning-project.pdf		machine-learning-project.pdf
magnitude_testing.py		magnitude_testing.py
normalizing_colors.py		normalizing_colors.py
parameters for logistic regression.txt		parameters for logistic regression.txt
report_1_csv_generation.py		report_1_csv_generation.py
report_1_feature_extraction_data.py		report_1_feature_extraction_data.py
report_1_feature_extraction_data_trying_stuff_out.py		report_1_feature_extraction_data_trying_stuff_out.py
report_1_image_operation_plots.py		report_1_image_operation_plots.py
report_2_color_channel_experiments.py		report_2_color_channel_experiments.py
report_2_finding_best_combination.py		report_2_finding_best_combination.py
report_2_hog_experiments.py		report_2_hog_experiments.py
report_2_results.py		report_2_results.py
results.txt		results.txt
score_calculation.py		score_calculation.py
simple_calculation_of_score.py		simple_calculation_of_score.py
split_color_perceived_classification.py		split_color_perceived_classification.py
split_color_perceived_classification_kfold_cross_validation.py		split_color_perceived_classification_kfold_cross_validation.py
split_color_perceived_frequency_classification.py		split_color_perceived_frequency_classification.py
split_color_perceived_frequency_classification_kfold_cross_validation.py		split_color_perceived_frequency_classification_kfold_cross_validation.py
ultimate.csv		ultimate.csv
ultimate2.csv		ultimate2.csv
ultimate3.csv		ultimate3.csv
ultimate4.csv		ultimate4.csv
util.py		util.py

Repository files navigation

De Bondt Harald
De Cremer Pieter
Goossens Rian
5/11/2015
==================================================
Relevant scripts for first deadline of competition
==================================================
- report_1_feature_extraction_data.py
	Calculates logloss for all our features and several combinations of them
- report_1_image_operation_plots.py
	Generates some of the plots in our report 

The other files are results of all our experiments throughout the semester and various utility modules. You can read these but they are not necessary for the report.