touch up
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@ -57,21 +57,29 @@ trainingFileNames, testFileNames = np.split(np.array(allFileNames), [int(len(all
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## Implementation
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Functions in garbageDumpSorting.py:
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* createSets - divides images between test and training set. This function should be run only once, unless the folders with training and test set are removed,
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```
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trainingFileNames, testFileNames = np.split(np.array(allFileNames), [int(len(allFileNames) * (1 - testRatio))])
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```
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* huMoments, haralick, histogram - calculate global feature descriptors,
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* processTrainData, processTestData - both work in the same way, they iterate over files in train or test directory, saves features as a matrix and then saves results to h5 file, it is recommended to run it only once as it takes some time to finish.
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```
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allFeatures = np.hstack([histo, hara, huMoments])
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```
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* trainAndTest - creates classifier, trains it and scores it,
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```
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clf = RandomForestClassifier(n_estimators=100, max_depth=15, random_state=9)
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```
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* classifyImage - predicts what kind of garbage is visible on a single image,
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```
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prediction = clf.predict(features)[0]
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```
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* sortDump - checks what kinds of trash are inside the garbage truck and their quantity, empties the garbage truck and sorts its contents on the garbage dump.
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