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