Identifying if image is human or dog and providing prediction on dog breed

human_dog_detect_classify.py

### Function that takes a path to an image as input
### and returns the dog breed that is predicted by the model.

def predict_breed(img_path):
    # extract bottleneck features
    bottleneck_feature = extract_Resnet50(path_to_tensor(img_path))
    # obtain predicted vector
    predicted_vector = new_model.predict(bottleneck_feature)
    # return dog breed that is predicted by the model
    return dog_names[np.argmax(predicted_vector)]

### Visualization function that shows the image of the dog and prints predicted dog breed
def check_dog_image(dog):
    image_show = cv2.imread(dog)
    image_show = cv2.cvtColor(image_show, cv2.COLOR_BGR2RGB)
    plt.imshow(image_show)
    
### Human Dog Detector Function (Goal function)
def human_dog_detector(img_path):
    '''
    Function to identify if a human face is identified or not, and provide a most likely
    dog breed that resembles the image, according to our model predictor (default = check_dog_image_VGG16).
    
    input img_path: path to image file
    input predictor: function that returns dog breed prediction according to a ML model
    output: None
    
    '''
    
    if face_detector(img_path): 
        print(f'This is probably a human!')
    else:
        print(f'We detected a dog!')
        
    check_dog_image(img_path)