Create drift detection workflow - completed

.github/workflows/drift-detection.yaml

@@ -50,17 +50,3 @@ jobs:
     - name: Data Drift Detection
       run: |
         python src/features/drift_detection.py
-
-    - name: Upload Log Artifact
-      uses: actions/upload-artifact@v3
-      with:
-        name: drift-detection
-        path: log/drift-detection.log
-
-    - name: Commit report
-      run: |
-        git status
-        git config --global user.name "github-actions[bot]"
-        git config --global user.email "github-actions[bot]@users.noreply.github.com"
-        git commit -am "Automated drift detection logs"
-        git push

src/features/drift_detection.py

@@ -49,16 +49,6 @@ def get_alibi_features(
 	grays_test = [cv2.cvtColor(i, cv2.COLOR_BGR2GRAY).flatten() for i in samples_test]
 	hists_test = [np.histogram(i, 256, [0, 256])[0] for i in grays_test]
 
-	alpha = .6
-	beta = 3
-
-	fake = {}
-	fake['imgs'] = [cv2.convertScaleAbs(img, alpha=alpha, beta=beta) for img in samples_test]
-	fake['grays'] = [cv2.cvtColor(i, cv2.COLOR_BGR2GRAY).flatten() for i in fake['imgs']]
-	fake['hists'] = [np.histogram(i, 256, [0, 256])[0] for i in fake['grays']]
-	hists_test = fake['hists']
-
-
 	print('>>> (3/5) Computing training features...')
 	hist_avg_train = [i / len(hists_train) for i in list(map(sum, zip(*hists_train)))]
 	print('>>> (4/5) Computing testing features...')