def compute_test_accuracy(X_test, Y_test, model, prediction_type, cellgroup_map_array):
prediction = model.predict(X_test)
auc = []
if prediction_type=="cellgroup":
prediction = np.dot(prediction, cellgroup_map_array)
Y_test = np.dot(Y_test, cellgroup_map_array)
mask = ~np.logical_or(Y_test.sum(1)==0, Y_test.sum(1)==Y_test.shape[1])
for y,pred in zip(Y_test.T,prediction.T):
pos = np.logical_and(mask, y==1)
neg = np.logical_and(mask, y==0)
try:
U = stats.mannwhitneyu(pred[pos], pred[neg])[0]
auc.append(1.-U/(np.count_nonzero(pos)*np.count_nonzero(neg)))
except ValueError:
auc.append(0.5)
return auc
python类predict()的实例源码
def test_file():
count = 1
face_cascade = cv2.CascadeClassifier(
'/usr/local/opt/opencv3/share/OpenCV/haarcascades/haarcascade_frontalface_default.xml')
argvs = sys.argv
for argv in argvs[1:]:
img = cv2.imread(argv)
if type(img) != str:
try:
gray = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)
print('convert succeed')
except:
print('can not convert to gray image')
continue
faces = face_cascade.detectMultiScale(gray, 1.3, 5)
for (x, y, w, h) in faces:
f = cv2.resize(gray[y:(y + h), x:(x + w)], (128, 128))
model = load_model('/Users/songheqi/model/model.h5')
num, acc = predict(model, f, 128)
name_list = read_name_list('/Users/songheqi/train_set/')
print('The {} picture is '.format(count) +
name_list[num] + ' acc : ', acc)
count += 1
def predict():
data = {}
try:
data = request.get_json()['data']
except KeyError:
return jsonify(status_code='400', msg='Bad Request'), 400
data = base64.b64decode(data)
image = io.BytesIO(data)
predictions = model.predict(image)
current_app.logger.info('Predictions: %s', predictions)
return jsonify(predictions=predictions)
def test_camera():
face_patterns = cv2.CascadeClassifier(
'/usr/local/opt/opencv3/share/OpenCV/haarcascades/haarcascade_frontalface_default.xml')
cameraCapture = cv2.VideoCapture(0)
success, frame = cameraCapture.read()
while True:
success, frame = cameraCapture.read()
gray = cv2.cvtColor(frame, cv2.COLOR_BGR2GRAY) # ????
faces = face_patterns.detectMultiScale(gray, 1.3, 5) # ????
for (x, y, w, h) in faces:
frame = cv2.rectangle(
frame, (x, y), (x + w, y + h), (255, 0, 0), 2) # ?????????????
f = cv2.resize(gray[y:(y + h), x:(x + w)], (128, 128))
model = load_model('/Users/songheqi/model/model.h5')
num, acc = predict(model, f, 128)
name_list = read_name_list('/Users/songheqi/train_set/')
print('You are ' + name_list[num] + ' acc : ', acc)
cv2.imshow("Camera", frame)
if cv2.waitKey(1) & 0xFF == ord('q'): # ?‘q’???
break
cameraCapture.release()
cv2.destroyAllWindows()
