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No models fix

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Arne van Iterson 2023-10-25 10:56:30 +02:00
parent a7b611c090
commit 17af113484
1 changed files with 12 additions and 7 deletions
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19
src/suite.py
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@ -360,9 +360,7 @@ class CVSuite:
# Normalise data using loaded scalers # Normalise data using loaded scalers
for idx, value in enumerate(data): for idx, value in enumerate(data):
d = np.array(value) d = np.array(value)
data[idx] = self.scaler[idx].transform(d.astype(np.float32).reshape(1, -1))[ data[idx] = self.scaler[idx].transform(d.astype(np.float32).reshape(1, -1))[0][0]
0
][0]
data = np.array([data], dtype=np.float32) data = np.array([data], dtype=np.float32)
@ -397,13 +395,19 @@ class CVSuite:
modelnr = (idx * 2) + idy modelnr = (idx * 2) + idy
guesses = self.models[modelnr][2] guesses = self.models[modelnr][2]
for guess in guesses:
print(guess)
# Convert guess array # Convert guess array
tag_true = [guess[0] for guess in guesses ] tag_true = [guess[0] for guess in guesses ]
tag_predict = [guess[1] for guess in guesses ] tag_predict = [guess[1] for guess in guesses ]
labels = [Tree(tag).name for tag in range(0, 8)] labels = [Tree(tag).name for tag in range(0, 8)]
sns.heatmap(confusion_matrix(tag_true, tag_predict), xticklabels=labels, yticklabels=labels, ax=graph, annot=True, cbar=False, fmt='g') cm = confusion_matrix(tag_true, tag_predict)
cmn = cmn = cm.astype('float') / cm.sum(axis=1)[:, np.newaxis]
sns.heatmap(cmn, xticklabels=labels, yticklabels=labels, ax=graph, annot=True, cbar=False, fmt='.2f')
graph.set_title(self.models[modelnr][0]) graph.set_title(self.models[modelnr][0])
graph.set_xlabel("Predicted") graph.set_xlabel("Predicted")
graph.set_ylabel("Actual") graph.set_ylabel("Actual")
@ -508,7 +512,7 @@ class CVSuite:
img_sobel = img_gray img_sobel = img_gray
self.canvas.add(img_sobel, "Sobel_edge") self.canvas.add(img_sobel, "Sobel_edge")
self.log.add("Sobel nonzero", cv2.countNonZero(img_sobel)) # self.log.add("Sobel nonzero", cv2.countNonZero(img_sobel))
# Canny edge # Canny edge
img_canny = cv2.Canny(image=img_blur, threshold1=ct1, threshold2=ct2) img_canny = cv2.Canny(image=img_blur, threshold1=ct1, threshold2=ct2)
@ -551,8 +555,9 @@ class CVSuite:
# Write results to CSV file # Write results to CSV file
if not part_update: if not part_update:
self.runTest(self.log.data) if self.models != []:
self.drawConfusionMatrix() self.runTest(self.log.data)
self.drawConfusionMatrix()
self.log.update() self.log.update()
else: else: