ship_detection_cut_test_img

def cutting(x, y):
    area_study = np.arange(3*80*80).reshape(3, 80, 80)
    for i in range(80):
        for j in range(80):
            area_study[0][i][j] = picture_tensor[0][y+i][x+j]
            area_study[1][i][j] = picture_tensor[1][y+i][x+j]
            area_study[2][i][j] = picture_tensor[2][y+i][x+j]
    area_study = area_study.reshape([-1, 3, 80, 80])
    area_study = area_study.transpose([0,2,3,1])
    area_study = area_study / 255
    sys.stdout.write('\rX:{0} Y:{1}  '.format(x, y))
    return area_study
    
def not_near(x, y, s, coordinates):
    result = True
    for e in coordinates:
        if x+s > e[0][0] and x-s < e[0][0] and y+s > e[0][1] and y-s < e[0][1]:
            result = False
    return result

def show_ship(x, y, acc, thickness=5):   
    for i in range(80):
        for ch in range(3):
            for th in range(thickness):
                picture_tensor[ch][y+i][x-th] = -1

    for i in range(80):
        for ch in range(3):
            for th in range(thickness):
                picture_tensor[ch][y+i][x+th+80] = -1
        
    for i in range(80):
        for ch in range(3):
            for th in range(thickness):
                picture_tensor[ch][y-th][x+i] = -1
        
    for i in range(80):
        for ch in range(3):
            for th in range(thickness):
                picture_tensor[ch][y+th+80][x+i] = -1