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Nayefleb commited on Apr 17

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7e42a78

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cropping.py +46 -0
gettingData.py +49 -0
sample.csv +1002 -0
segmentation.py +14 -0

cropping.py ADDED Viewed

	@@ -0,0 +1,46 @@

+def cropping(image, filename):
+    #Left Top Crop
+    crop = image[:96, :96]
+    crop = cv2.resize(crop, (128, 128))
+    cv2.imwrite(filename[:-4] + 'leftTop' + '.png', crop)
+    #Center Top Crop
+    crop = image[:96, 16:112]
+    crop = cv2.resize(crop, (128, 128))
+    cv2.imwrite(filename[:-4] + 'centerTop' + '.png', crop)
+    #Right Top Crop
+    crop = image[:96, 32:]
+    crop = cv2.resize(crop, (128, 128))
+    cv2.imwrite(filename[:-4] + 'rightTop' + '.png', crop)
+    #Left Center Crop
+    crop = image[16:112, :96]
+    crop = cv2.resize(crop, (128, 128))
+    cv2.imwrite(filename[:-4] + 'leftCenter' + '.png', crop)
+    #Center Center Crop
+    crop = image[16:112, 16:112]
+    crop = cv2.resize(crop, (128, 128))
+    cv2.imwrite(filename[:-4] + 'centerCenter' + '.png', crop)
+    #Right Center Crop
+    crop = image[16:112, 32:]
+    crop = cv2.resize(crop, (128, 128))
+    cv2.imwrite(filename[:-4] + 'rightCenter' + '.png', crop)
+    #Left Bottom Crop
+    crop = image[32:, :96]
+    crop = cv2.resize(crop, (128, 128))
+    cv2.imwrite(filename[:-4] + 'leftBottom' + '.png', crop)
+    #Center Bottom Crop
+    crop = image[32:, 16:112]
+    crop = cv2.resize(crop, (128, 128))
+    cv2.imwrite(filename[:-4] + 'centerBottom' + '.png', crop)
+    #Right Bottom Crop
+    crop = image[32:, 32:]
+    crop = cv2.resize(crop, (128, 128))
+    cv2.imwrite(filename[:-4] + 'rightBottom' + '.png', crop)

gettingData.py ADDED Viewed

	@@ -0,0 +1,49 @@

+def get_records():
+    """ Get paths for data in data/mit/ directory """
+    #Download if doesn't exist
+    # There are 3 files for each record
+    # *.atr is one of them
+    paths = glob('/path/to/MITDB/dataset/*.atr')
+    # Get rid of the extension
+    paths = [path[:-4] for path in paths]
+    paths.sort()
+    return paths
+def beat_annotations(annotation):
+    """ Get rid of non-beat markers """
+    """'N' for normal beats. Similarly we can give the input 'L' for left bundle branch block beats. 'R' for right bundle branch block
+        beats. 'A' for Atrial premature contraction. 'V' for ventricular premature contraction. '/' for paced beat. 'E' for Ventricular
+        escape beat."""
+    good = ['N']
+    ids = np.in1d(annotation.symbol, good)
+    # We want to know only the positions
+    beats = annotation.sample[ids]
+    return beats
+ def segmentation(records):
+    Normal = []
+    for e in records:
+        signals, fields = wfdb.rdsamp(e, channels = [0])
+        ann = wfdb.rdann(e, 'atr')
+        good = ['N']
+        ids = np.in1d(ann.symbol, good)
+        imp_beats = ann.sample[ids]
+        beats = (ann.sample)
+        for i in imp_beats:
+            beats = list(beats)
+            j = beats.index(i)
+            if(j!=0 and j!=(len(beats)-1)):
+                x = beats[j-1]
+                y = beats[j+1]
+                diff1 = abs(x - beats[j])//2
+                diff2 = abs(y - beats[j])//2
+                Normal.append(signals[beats[j] - diff1: beats[j] + diff2, 0])
+    return Normal

sample.csv ADDED Viewed

	@@ -0,0 +1,1002 @@

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segmentation.py ADDED Viewed

	@@ -0,0 +1,14 @@

+data = np.array(csv_data)
+signals = []
+count = 1
+peaks =  biosppy.signals.ecg.christov_segmenter(signal=data, sampling_rate = 200)[0]
+for i in (peaks[1:-1]):
+    diff1 = abs(peaks[count - 1] - i)
+    diff2 = abs(peaks[count + 1]- i)
+    x = peaks[count - 1] + diff1//2
+    y = peaks[count + 1] - diff2//2
+    signal = data[x:y]
+    signals.append(signal)
+    count += 1
+return signals