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")