def test_transplant2(self): """To use on server. Passes binary data to input, and passes io.BytesIO instance to output """ o = io.BytesIO() pyxif.transplant(I1, I2, o) self.assertEqual(pyxif.load(I1), pyxif.load(o.getvalue())) try: i = Image.open(o) i._getexif() except: self.fail("'transplant' generated wrong file") finally: i.close()
def test_transplant2(self): """To use on server. Passes binary data to input, and passes io.BytesIO instance to output """ o = io.BytesIO() pyxif.transplant(I1, I2, o) self.assertEqual(pyxif.load(I1), pyxif.load(o.getvalue())) try: i = Image.open(o) i._getexif() except: self.fail("'transplant' generated wrong file") finally: i.close()
def process_clahe(in_path, tileGridSize, grey=False, out_path="", clip_limit=2): """ Appy CLAHE (contrast limited adaptive histogram equalization) method on an image for more information about CLAHE, see https://docs.opencv.org/3.1.0/d5/daf/tutorial_py_histogram_equalization.html Overwriting image will raise an error, as the initial image is needed to copy-past metadata :param in_path: input image :param tileGridSize: size of the "blocks" to apply local histogram equalization :param grey: if True, the image will be converted to grayscale :param out_path: output path, the folders must exists and the image extension must be valid by default, output will be saved as input_path/input_name_clahe.JPG :param clip_limit: contrast limit, used to avoid too much noise """ if out_path == "": out_path = ".".join(in_path.split(".")[:-1]) + "_clahe.JPG" # read input print("Processing CLAHE method on " + in_path.split("/")[-1]) img = cv.imread(in_path) # convert color to gray if grey: img = cv.cvtColor(img, cv.COLOR_BGR2GRAY) # apply a median filter before clahe img = cv.medianBlur(img, 3) # create clahe object clahe = cv.createCLAHE(clipLimit=clip_limit, tileGridSize=(tileGridSize, tileGridSize)) # CLAHE # apply CLAHE for each image channel, and then recreate the full image (only useful if gray==False) channels_ini = cv.split(img) channels_final = [] for channel in channels_ini: # Apply CLAHE channels_final.append(clahe.apply(channel)) img_final = cv.merge(channels_final) # save image and write metadata from initial file cv.imwrite(out_path, img_final) pyxif.transplant(in_path, out_path)
def test_transplant(self): pyxif.transplant(INPUT_FILE1, INPUT_FILE2, "transplant.jpg") exif_src = pyxif.load(INPUT_FILE1) img_src = pyxif.load(INPUT_FILE2) generated = pyxif.load("transplant.jpg") self.assertEqual(exif_src, generated) self.assertNotEqual(img_src, generated) try: i = Image.open("transplant.jpg") i._getexif() except: self.fail("'transplant' generated wrong file") finally: i.close() with self.assertRaises(ValueError): pyxif.transplant(NOEXIF_FILE, INPUT_FILE2, "foo.jpg")
def test_transplant(self): pyxif.transplant(INPUT_FILE1, INPUT_FILE2, "transplant.jpg") exif_src = pyxif.load(INPUT_FILE1) img_src = pyxif.load(INPUT_FILE2) generated = pyxif.load("transplant.jpg") self.assertEqual(exif_src, generated) self.assertNotEqual(img_src, generated) try: i = Image.open("transplant.jpg") i._getexif() except: self.fail("'transplant' generated wrong file") finally: i.close() with self.assertRaises(ValueError): pyxif.transplant(NOEXIF_FILE, INPUT_FILE2, "foo.jpg")
def transplant_sample(): pyxif.transplant(os.path.join("samples", "01.jpg"), os.path.join("samples", "02.jpg"), "transplant_sample.jpg")