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How to use update_image method in tempest

Best Python code snippet using tempest_python

Enemy.py

Source:Enemy.py

...140        frame = int(self.time / (Enemy.CYCLE / ENEMY_IMAGE_LENGTH))141        if frame != self.frame:142                self.frame = frame143                if (self.face == 'r'):144                    self.update_image(self.IMAGES_RIGHT)145                elif (self.face == 'u'):146                    self.update_image(self.IMAGES_BACK)147                elif (self.face == 'l'):148                    self.update_image(self.IMAGES_LEFT)149                elif (self.face == 'd'):150                    self.update_image(self.IMAGES_FRONT)151                elif(self.face == 'rs'):152                    self.image = self.IMAGES_RIGHT[0]153                elif(self.face == 'us'):154                    self.image = self.IMAGES_BACK[0]155                elif(self.face == 'ls'):156                    self.image = self.IMAGES_LEFT[0]157                elif(self.face == 'ds'):158                    self.image = self.IMAGES_FRONT[0]159                else:160                    self.image = self.front_image.convert_alpha()161        self.dirty = 1162    def set_face(self, Enemy_face):163        if Enemy_face == 'u':164            self.update_image(self.IMAGES_FRONT)165            self.face = 'd'166        elif Enemy_face == 'd':167            self.update_image(self.IMAGES_BACK)168            self.face = 'u'169        elif Enemy_face == 'l':170            self.update_image(self.IMAGES_RIGHT)171            self.face = 'r'172        elif Enemy_face == 'r':173            self.update_image(self.IMAGES_LEFT)174            self.face = 'l'175        elif(self.face == 'rs'):176            self.update_image(self.IMAGES_LEFT)177        elif(self.face == 'us'):178            self.update_image(self.IMAGES_FRONT)179        elif(self.face == 'ls'):180            self.update_image(self.IMAGES_RIGHT)181        elif(self.face == 'ds'):182            self.update_image(self.IMAGES_BACK)183    def load_images_helper(self, imageArray, sheet):184        # key = sheet.get_at((0,0))185        # hereeeeee186        alphabg = (23, 23, 23)187        for i in range(0, 4):188            surface = PG.Surface((100, 100))189            surface.set_colorkey(alphabg)190            surface.blit(sheet, (0, 0), (i*100, 0, 100, 100))191            imageArray.append(surface)192        return imageArray193    # this will all end up in the key handler194    def update_image(self, imageArray):195        try:196            self.image = imageArray[self.frame].convert_alpha()197        except IndexError:198            self.image = self.front_image.convert_alpha()...

camera_tool.py

Source:camera_tool.py

...22K = 10723L = 10824def normalize_in_range(value, min, max, b_range):25    return (((value - 0) * (max - min)) / (b_range - 0)) + min26def update_image(val):27    record_params = cv2.getTrackbarPos('Record params', title_window)28    fp = cv2.getTrackbarPos('Focal length', title_window)29    tilt_angle = cv2.getTrackbarPos('Tilt angle', title_window)30    pan_angle = cv2.getTrackbarPos('Pan angle', title_window)31    roll_angle = cv2.getTrackbarPos('Roll angle', title_window)32    xloc = cv2.getTrackbarPos('Camera loc x', title_window)33    yloc = cv2.getTrackbarPos('Camera loc y', title_window)34    zloc = cv2.getTrackbarPos('Camera loc z', title_window)35    fp = normalize_in_range(fp, 1000, 6000, bar_range)36    xloc = normalize_in_range(xloc, 46.2, 57.2, bar_range)37    yloc = normalize_in_range(yloc, -66.07020, -16.74178, bar_range)38    zloc = normalize_in_range(zloc, 10.1387, 23.01126, bar_range)39    zloc = yloc * (-.4)40    tilt_angle = normalize_in_range(tilt_angle, -20., -5., bar_range)41    pan_angle = normalize_in_range(pan_angle, -60., 60., pan_bar_range)42    roll_angle = normalize_in_range(roll_angle, -1., 1., bar_range)43    params = np.array([44        image_center_x,45        image_center_y,46        fp,47        tilt_angle,48        pan_angle,49        roll_angle,50        xloc,51        yloc,52        zloc53    ])54    if record_params == 1:55        camera_samples.append(params)56    base_rotation = RotationUtil.rotate_y_axis(0) @ RotationUtil.rotate_z_axis(roll_angle) @ \57                    RotationUtil.rotate_x_axis(-90)58    pan_tilt_rotation = RotationUtil.pan_y_tilt_x(pan_angle, tilt_angle)59    rotation = pan_tilt_rotation @ base_rotation60    rot_vec, _ = cv2.Rodrigues(rotation)61    tilt, pan, roll = rot_vec[0].item(), rot_vec[1].item(), rot_vec[2].item()62    camera_params = np.array([63        image_center_x,64        image_center_y,65        fp,66        tilt,67        pan,68        roll,69        xloc,70        yloc,71        zloc72    ])73    camera = Camera(camera_params)74    homography = camera.homography()75    edge_map = edge_map_from_homography(homography,76                                        binary_court,77                                        image_resolution)78    # im = cv2.imread('court.jpg')79    # edge_map2 = cv2.warpPerspective(im, homography, image_resolution, flags=cv2.INTER_LINEAR)80    text = f"focal length: {round(camera.focal_length, 3)} \n" \81           f"cam_loc_X: {round(camera.camera_center_x, 3)} \n" \82           f"cam_loc_Y: {round(camera.camera_center_y, 3)} \n" \83           f"cam_loc_Z: {round(camera.camera_center_z, 3)} \n" \84           f"tilt: {round(tilt_angle, 3):.3f} \n" \85           f"pan: {round(pan_angle, 3):.3f} \n" \86           f"roll: {round(roll_angle, 3):.3f} \n"87    y0, dy = 30, 2088    for i, line in enumerate(text.split('\n')):89        y = y0 + i * dy90        cv2.putText(edge_map, line, (20, y),91                    cv2.FONT_HERSHEY_SIMPLEX, .5, (255, 255, 255))92    cv2.putText(edge_map, f'{np.round(homography[0,0], 3):<8} {np.round(homography[0,1], 3):=10} {np.round(homography[0,2], 3):>10}', (900, 30), cv2.FONT_HERSHEY_SIMPLEX, .5, (255, 255, 255))93    cv2.putText(edge_map, f'{np.round(homography[1,0], 3):<8} {np.round(homography[1,1], 3):=10} {np.round(homography[1,2], 3):>10}', (900, 50), cv2.FONT_HERSHEY_SIMPLEX, .5, (255, 255, 255))94    cv2.putText(edge_map, f'{np.round(homography[2,0], 3):<8} {np.round(homography[2,1], 3):=10} {np.round(homography[2,2], 3):>10}', (900, 70), cv2.FONT_HERSHEY_SIMPLEX, .5, (255, 255, 255))95    cv2.circle(edge_map, (int(camera.image_center_x), int(camera.image_center_y)), 2, (0, 255, 0), 3)96    cv2.putText(edge_map, f'Samples:{len(camera_samples)}', (600, y0), cv2.FONT_HERSHEY_SIMPLEX, .5, (255, 255, 255))97    cv2.imshow(title_window, edge_map)98def save_camera_samples():99    samples = np.array(camera_samples)100    timestamp = datetime.now().strftime("%Y_%m_%d_%H_%M_%S")101    num_of_samples = len(camera_samples)102    filename = f'saved_camera_param_data/{timestamp}-{num_of_samples}.npy'103    np.save(filename, samples)104if __name__ == '__main__':105    image_resolution = (1280, 720)106    image_center_x = image_resolution[0]/2107    image_center_y = image_resolution[1]/2108    focal_point = 0109    tilt_angle = int(bar_range / 2)110    pan_angle = int(pan_bar_range / 2)111    roll_angle = int(bar_range / 2)112    camera_loc_x = int(bar_range * .57)113    camera_loc_y = int(bar_range / 2)114    camera_loc_z = int(bar_range / 2)115    record_params = 0116    title_window = 'Camera Tool'117    binary_court = sio.loadmat('worldcup2014.mat')118    cv2.namedWindow(title_window)119    cv2.createTrackbar('Record params', title_window, record_params, 1, update_image)120    cv2.createTrackbar('Focal length', title_window, focal_point, bar_range, update_image)121    cv2.createTrackbar('Tilt angle', title_window, tilt_angle, bar_range, update_image)122    cv2.createTrackbar('Pan angle', title_window, pan_angle, pan_bar_range, update_image)123    cv2.createTrackbar('Roll angle', title_window, roll_angle, bar_range, update_image)124    cv2.createTrackbar('Camera loc x', title_window, camera_loc_x, bar_range, update_image)125    cv2.createTrackbar('Camera loc y', title_window, camera_loc_y, bar_range, update_image)126    cv2.createTrackbar('Camera loc z', title_window, camera_loc_z, bar_range, update_image)127    update_image(1)128    while 1:129        key = cv2.waitKey(0)130        if key == Q:    # quit131            break132        elif key == W:133            val = cv2.getTrackbarPos('Tilt angle', title_window)134            cv2.setTrackbarPos('Tilt angle', title_window, val+1)135            update_image(1)136        elif key == S:137            val = cv2.getTrackbarPos('Tilt angle', title_window)138            cv2.setTrackbarPos('Tilt angle', title_window, val - 1)139            update_image(1)140        elif key == A:141            val = cv2.getTrackbarPos('Pan angle', title_window)142            cv2.setTrackbarPos('Pan angle', title_window, val - 1)143            update_image(1)144        elif key == D:145            val = cv2.getTrackbarPos('Pan angle', title_window)146            cv2.setTrackbarPos('Pan angle', title_window, val + 1)147            update_image(1)148    if len(camera_samples) > 0:149        save_camera_samples()150        print('Camera samples saved!')...

Image.py

Source:Image.py

1"""2#####################################3## IT 441 Computer Graphics4## Instructor:Nitin Raje5## Implemented By: Shalin Shah6## ID : 2011011797#####################################8"""910from PIL import Image11from PIL import ImageChops12from PIL import ImageFilter13import webbrowser14from PIL import ImageDraw   1516def genTriangle(data, steps, update_image, k):17    '''18    The triangle and it's subtriangle is calculated here.19    '''20    # draw triangles each step through21    update_image.line((data[0], data[1]))22    update_image.line((data[1], data[2]))23    update_image.line((data[0], data[2]))24    25    # next triangle formed by connecting the midpoints of each of the sides26    x1 = (data[0][0] + data[1][0]) / 227    y1 = (data[0][1] + data[1][1]) / 228    29    x2 = (data[1][0] + data[2][0]) / 230    y2 = (data[1][1] + data[2][1]) / 231    32    x3 = (data[2][0] + data[0][0]) / 233    y3 = (data[2][1] + data[0][1]) / 234    35    # updates data in next recursion36    data2 = ((x1, y1), (x2, y2), (x3, y3))37    38    # loop through until step limit is reached39    k += 140    if k <= steps:41        genTriangle((data[0], data2[0], data2[2]), steps, update_image, k)42        genTriangle((data[1], data2[0], data2[1]), steps, update_image, k)43        genTriangle((data[2], data2[1], data2[2]), steps, update_image, k)4445def draw(image):46    return ImageDraw.Draw(image)4748# higher steps gives more detail49# test with values of 1 to 1050steps = 65152# the three x,y data points for the starting equilateral triangle53data = ((0, 400), (400, 400), (200, 0))5455# picture canvas creation uses size tuple given in data[1]56size = data[1]57picture = Image.new('1', size, color="red")58update_image = draw(picture)5960# draw the triangle and calculate next triangle corner coordinates61genTriangle(data, steps, update_image, 0)6263# save the final image file and then view with an image viewer64imagename = "TRIANGLE_ORIGINAL.jpg"65picture.save(imagename);6667im1 = Image.open("TRIANGLE_ORIGINAL.jpg")6869im2 = im1.filter(ImageFilter.BLUR)70im2.save('TRIANGLE_BLURRED.jpg',"JPEG")7172ImageChops.invert(im1)73im3 = im1.filter(ImageFilter.EMBOSS)74im3.save('TRIANGLE_EMBOSSED_INVERTED.jpg',"JPEG")
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