image_path = "fasterRCNN/faster-rcnn-keras-master/img/street.jpg";

from PIL import Image
import numpy as np
image = Image.open(image_path) # RGB
tmp_image = np.array(image)
print("PIL open shape:",tmp_image.shape, tmp_image)


# load with cv2
import cv2
image = cv2.imread(image_path)  # mode: BGR
print("cv2 imread shape:", image.shape) # (width,height,channel)


# load with matplotlib
import matplotlib.image as mpimg
image = mpimg.imread(image_path) #  mode: RGB
print("matplotlib imread shape:",image.shape, image) # ( height, width,channel(RGB) )

def my_sum(*args):
    result = 0
    # Iterating over the Python args tuple
    for x in args:
        result += x
    return result

print(my_sum(1, 2, 3))
# output: 6

def print_three_things(a, b, c):
    print( 'a = {0}, b = {1}, c = {2}'.format(a,b,c))

mylist = ['aardvark', 'baboon', 'cat']
print_three_things(*mylist)
# output: a = aardvark, b = baboon, c = cat

Macintosh HD > Applications > Python3.6 (或者其它安装python目录）
然后：双击 Install Certificates.command

class ImageUtils:

	def __init__(self):
		import numpy;
		self.np = numpy;
		pass

	## 
	def resizePadding(self, np_2d_image, target_width,target_height):
		single_img 		= np_2d_image;
		tmp_img_width 	= single_img.shape[1]
		tmp_img_height 	= single_img.shape[0]
		np 				= self.np
		print("resizeFile origin shape :",single_img.shape)
		# 宽度pading添加
		if tmp_img_width < target_width:
			for x in range(tmp_img_width, target_width):
				# tmp_arr    = np.arange(255,255,(len(single_img),1));
				if x%2 == 0:
					single_img = np.insert(single_img, 0, 255,axis=1);
				else:
					single_img = np.insert(single_img, single_img.shape[1], 255,axis=1);
				# print(file_name_prefix, "origin shape :",single_img.shape)
		# 高度pading添加
		if tmp_img_height < target_height:
			for x in range(tmp_img_height, target_height):
				# tmp_arr    = np.arange(255,255,(len(single_img),1));
				if x%2 == 0:
					single_img = np.insert(single_img, 0, 255,axis=0);
				else:
					single_img = np.insert(single_img, single_img.shape[0], 255,axis=0);

		# 宽度截掉
		if tmp_img_width > target_width:
			for x in range(target_width, tmp_img_width):
				if x%2 == 0:
					single_img = np.delete(single_img, 0, axis=1);
				else:
					single_img = np.delete(single_img, single_img.shape[1]-1, axis=1);

		# 高度截掉
		if tmp_img_height > target_height:
			for x in range(target_height, tmp_img_height):
				if x%2 == 0:
					single_img = np.delete(single_img, 0, axis=0);
				else:
					single_img = np.delete(single_img, single_img.shape[0]-1, axis=0);


		print("resizeFile after shape :",single_img.shape)
		return single_img;