def test_gray():
img_path = os.path.join(here, 'data', 'green_fish.jpg')
img = caer.imread(img_path, gray=True)
img_chann = caer.imread(img_path,
channels=1) # Maintain backwards-compatibility
assert len(img.shape) == 2
assert len(img_chann.shape) == 2
def test_target_sizes():
test_img = os.path.join(here, 'caer', 'data', 'bear.jpg')
img_400_400 = caer.imread(test_img, target_size=(400, 400))
img_300_300 = caer.imread(test_img, target_size=(300, 300))
img_199_206 = caer.imread(test_img, target_size=(199, 206))
assert img_400_400.shape[:2] == (400, 400)
assert img_300_300.shape[:2] == (300, 300)
assert img_199_206.shape[:2] == (199, 206)
def test_imread_target_sizes():
img_path = os.path.join(here, 'data', 'beverages.jpg')
img_400_400 = caer.imread(img_path, target_size=(400, 400))
img_304_339 = caer.imread(img_path, target_size=(304, 339))
img_199_206 = caer.imread(img_path, target_size=(199, 206))
assert img_400_400.shape[:2] == (400, 400)
assert img_304_339.shape[:2] == (
339, 304
) # Numpy arrays are processed differently (h,w) as opposed to (w,h)
assert img_199_206.shape[:2] == (
206, 199
) # Numpy arrays are processed differently (h,w) as opposed to (w,h)
def test_imread_target_sizes():
tens_400_400 = caer.imread(tens_path, target_size=(400, 400))
tens_304_339 = caer.imread(tens_path, target_size=(304, 339))
tens_199_206 = caer.imread(tens_path, target_size=(199, 206))
assert tens_400_400.shape[:2] == (400, 400)
assert tens_304_339.shape[:2] == (
339, 304
) # Numpy arrays are processed differently (h,w) as opposed to (w,h)
assert tens_199_206.shape[:2] == (
206, 199
) # Numpy arrays are processed differently (h,w) as opposed to (w,h)
assert isinstance(tens_400_400, caer.Tensor)
assert isinstance(tens_304_339, caer.Tensor)
assert isinstance(tens_199_206, caer.Tensor)
def test_imread():
cv_bgr = cv.imread(tens_path)
cv_rgb = cv.cvtColor(cv_bgr.copy(), cv.COLOR_BGR2RGB)
caer_bgr = caer.imread(tens_path, rgb=False) # Expected: BGR
caer_rgb = caer.imread(tens_path, rgb=True) # Expected: RGB
# caer_rgbF_grayF = caer.imread(tens_path, rgb=False, gray=False) # Expected: BGR
# caer_rgbT_grayF = caer.imread(tens_path, rgb=True, gray=False) # Expected: RGB
# caer_rgbT_grayT = caer.imread(tens_path, rgb=True, gray=True) # Expected: Gray
# caer_rgbF_grayT = caer.imread(tens_path, rgb=False, gray=True) # Expected: Gray
# caer_rgbT_grayT = caer.imread(tens_path, rgb=True, gray=True) # Expected: Gray
# Asserts
assert np.all(caer_bgr == cv_bgr)
assert np.all(caer_rgb == cv_rgb)
def test_imread():
test_img = os.path.join(here, 'caer', 'data', 'bear.jpg')
img = caer.imread(test_img)
test_against = cv.imread(test_img)
assert np.all(img == test_against)
def test_keep_aspect_ratio():
test_img = os.path.join(here, 'caer', 'data', 'sunrise.jpg')
img_400_400 = caer.imread(test_img,
target_size=(400, 400),
keep_aspect_ratio=True)
img_223_182 = caer.imread(test_img,
target_size=(223, 182),
keep_aspect_ratio=True)
img_93_35 = caer.imread(test_img,
target_size=(93, 35),
keep_aspect_ratio=True)
assert img_400_400.shape[:2] == (400, 400)
assert img_223_182.shape[:2] == (223, 182)
assert img_93_35.shape[:2] == (93, 35)
def test_imread():
img_path = os.path.join(here, 'data', 'beverages.jpg')
cv_bgr = cv.imread(img_path)
cv_rgb = cv.cvtColor(cv_bgr.copy(), cv.COLOR_BGR2RGB)
cv_gray = cv.cvtColor(cv_bgr.copy(), cv.COLOR_BGR2GRAY)
caer_bgr = caer.imread(img_path, rgb=False) # Expected: BGR
caer_rgb = caer.imread(img_path, rgb=True) # Expected: RGB
caer_rgbF_grayF = caer.imread(img_path, rgb=False,
gray=False) # Expected: BGR
caer_rgbT_grayF = caer.imread(img_path, rgb=True,
gray=False) # Expected: RGB
caer_rgbT_grayT = caer.imread(img_path, rgb=True,
gray=True) # Expected: Gray
caer_rgbF_grayT = caer.imread(img_path, rgb=False,
gray=True) # Expected: Gray
caer_rgbT_grayT = caer.imread(img_path, rgb=True,
gray=True) # Expected: Gray
# Asserts
assert np.all(caer_bgr == cv_bgr)
assert np.all(caer_rgb == cv_rgb)
assert np.all(caer_rgbF_grayF == cv_bgr)
assert np.all(caer_rgbT_grayF == cv_rgb)
assert np.all(caer_rgbT_grayT == cv_gray)
assert np.all(caer_rgbF_grayT == cv_gray)
assert np.all(caer_rgbT_grayT == cv_gray)
def test_imread_preserve_aspect_ratio():
img_path = os.path.join(here, 'data', 'green_fish.jpg')
img_400_400 = caer.imread(img_path,
target_size=(400, 400),
preserve_aspect_ratio=True)
img_223_182 = caer.imread(img_path,
target_size=(223, 182),
preserve_aspect_ratio=True)
img_93_35 = caer.imread(img_path,
target_size=(93, 35),
preserve_aspect_ratio=True)
assert img_400_400.shape[:2] == (400, 400)
assert img_223_182.shape[:2] == (
182, 223
) # Numpy arrays are processed differently (h,w) as opposed to (w,h)
assert img_93_35.shape[:2] == (
35, 93
) # Numpy arrays are processed differently (h,w) as opposed to (w,h)
def test_imread_preserve_aspect_ratio():
tens_400_400 = caer.imread(tens_path,
target_size=(400, 400),
preserve_aspect_ratio=True)
tens_223_182 = caer.imread(tens_path,
target_size=(223, 182),
preserve_aspect_ratio=True)
tens_93_35 = caer.imread(tens_path,
target_size=(93, 35),
preserve_aspect_ratio=True)
assert tens_400_400.shape[:2] == (400, 400)
assert tens_223_182.shape[:2] == (
182, 223
) # Numpy arrays are processed differently (h,w) as opposed to (w,h)
assert tens_93_35.shape[:2] == (
35, 93
) # Numpy arrays are processed differently (h,w) as opposed to (w,h)
assert isinstance(tens_400_400, caer.Tensor)
assert isinstance(tens_223_182, caer.Tensor)
assert isinstance(tens_93_35, caer.Tensor)
def test_gray():
test_img = os.path.join(here, 'caer', 'data', 'blue_tang.jpg')
img = caer.imread(test_img, channels=1)
assert len(img.shape) == 2
def show_original_image(*args):
global currentImage
global previous_image
global reload_local_file
global popup_menu_image
global image_size
global resizedImgBtn
global rotateImgBtn
user_cancelled_or_error = False
if resizedImgBtn['bg'] == 'lightblue':
resizedImgBtn['bg'] = 'lightgrey'
else:
rotateImgBtn['bg'] = 'lightgrey'
selectedImage = imageSelection.get()
previous = lblFileName['text']
lblFileName['text'] = ''
lblError['text'] = ''
if selectedImage == 'Open File >>':
if not reload_local_file:
all_ext = ('All files', '*.*')
png_ext = ('PNG files', '.png')
jpg_ext = ('JPG files', '.jpg .jpeg')
bmp_ext = ('BMP files', '.bmp')
tiff_ext = ('TIFF files', '.tif .tiff')
try:
img_filename = fd.askopenfilename(filetypes=(all_ext, png_ext,
jpg_ext, bmp_ext,
tiff_ext))
if img_filename != '':
lblFileName['text'] = img_filename
currentImage = caer.imread(img_filename)
else:
# user clicked 'Cancel' button
user_cancelled_or_error = True
except Exception as e:
lblError['text'] = 'Error'
user_cancelled_or_error = True
print(str(e))
else:
reload_local_file = False
lblFileName['text'] = previous
elif selectedImage == 'Mountain':
currentImage = caer.data.mountain(rgb=True)
elif selectedImage == 'Snow':
currentImage = caer.data.snow(rgb=True)
elif selectedImage == 'Sunrise':
currentImage = caer.data.sunrise(rgb=True)
elif selectedImage == 'Night':
currentImage = caer.data.night(rgb=True)
elif selectedImage == 'Island':
currentImage = caer.data.island(rgb=True)
elif selectedImage == 'Puppies':
currentImage = caer.data.puppies(rgb=True)
elif selectedImage == 'Black Cat':
currentImage = caer.data.black_cat(rgb=True)
elif selectedImage == 'Sea Turtle':
currentImage = caer.data.sea_turtle(rgb=True)
elif selectedImage == 'Gold Fish':
currentImage = caer.data.gold_fish(rgb=True)
elif selectedImage == 'Bear':
currentImage = caer.data.bear(rgb=True)
elif selectedImage == 'Beverages':
currentImage = caer.data.beverages(rgb=True)
elif selectedImage == 'Tent':
currentImage = caer.data.tent(rgb=True)
elif selectedImage == 'Camera':
currentImage = caer.data.camera(rgb=True)
else:
currentImage = caer.data.guitar(rgb=True)
if not user_cancelled_or_error:
image_size = [
str(int(currentImage.width())),
str(int(currentImage.height()))
]
selectedSize.set(image_size[0] + 'x' + image_size[1])
reset_ghsps()
image_show(currentImage)
else:
lblFileName['text'] = previous
imageSelection.set(previous_image)
popup_menu_image['bg'] = 'green'
popup_menu_image['bg'] = 'lightgreen'
selectedImage = previous_image
previous_image = selectedImage
# | |___ / ____ \ | |____ | | \ \ http://github.com/jasmcaus/caer
# \_____\/_/ \_ \______ |_| \_\
# Licensed under the MIT License <http://opensource.org/licenses/MIT>
# SPDX-License-Identifier: MIT
# Copyright (c) 2020-21 The Caer Authors <http://github.com/jasmcaus>
import caer
import cv2 as cv
import os
here = os.path.dirname(os.path.dirname(__file__))
tens_path = os.path.join(here, 'data', 'green_fish.jpg')
cv_tens = cv.imread(tens_path)
caer_tens = caer.imread(tens_path)
def test_target_sizes():
# Should return <ndarray>s
tens_400_400 = caer.resize(cv_tens, target_size=(400,400))
tens_304_339 = caer.resize(cv_tens, target_size=(304,339))
tens_199_206 = caer.resize(cv_tens, target_size=(199,206))
# Should return <caer.Tensor>s
caer_tens_400_400 = caer.resize(caer_tens, target_size=(400,400))
caer_tens_304_339 = caer.resize(caer_tens, target_size=(304,339))
caer_tens_199_206 = caer.resize(caer_tens, target_size=(199,206))
assert tens_400_400.shape[:2] == (400,400)
assert tens_304_339.shape[:2] == (339,304)
def test_gray():
test_img = os.path.join(here, 'data', 'green_fish.jpg')
img = caer.imread(test_img, channels=1)
assert len(img.shape) == 2
