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stream=sys.stdout) + log.info("Hello image filtering") + args = build_argparse().parse_args() + + image_path = args.input_path + log.info(args.input_path) + + image = cv2.imread(image_path) + my_filter = ImageFilter(grey=True, shape=None, crop=True) + + cv2.imshow("Image1", image) + cv2.imshow("Image2", my_filter.process_image(image)) + cv2.waitKey(0) + cv2.destroyAllWindows() + + return + + +if __name__ == '__main__': + sys.exit(main()) diff --git a/samples/practice2_anastasia_funkner.py b/samples/practice2_anastasia_funkner.py new file mode 100644 index 0000000..721b61e --- /dev/null +++ b/samples/practice2_anastasia_funkner.py @@ -0,0 +1,34 @@ +import sys +import cv2 +import argparse +import logging as log + +sys.path.append('../src') +from ie_detector import InferenceEngineDetector + + +def build_argparse(): + parser = argparse.ArgumentParser() + + # + # Add your code here + # + + return parser + + +def main(): + log.basicConfig(format="[%(levelname)s] %(message)s", level=log.INFO, + stream=sys.stdout) + log.info("Hello object detection!") + args = build_argparse().parse_args() + + # + # Add your code here + # + + return + + +if __name__ == '__main__': + sys.exit(main()) diff --git a/src/imagefilter.py b/src/imagefilter.py index 09d8c2f..c4357be 100644 --- a/src/imagefilter.py +++ b/src/imagefilter.py @@ -1,18 +1,36 @@ import cv2 + class ImageFilter(): - def __init__(self, gray = False, shape = None, crop = None): - self.gray = gray + def __init__(self, grey=False, shape=None, crop=None): + self.grey = grey + self.crop = crop + if shape: self.shape = shape - if crop: - self.crop = crop - + else: + self.shape = None + def process_image(self, image): - # - # Put your code here, like example - # - #if self.shape: - # do something - # - return image \ No newline at end of file + + if self.grey: + image = cv2.cvtColor(image, cv2.COLOR_BGR2GRAY) + + if self.shape is not None: + image = cv2.resize(image, dsize=self.shape) + + if self.crop: + two_size = image.shape[:2] + min_size = min(two_size) + new_slice = [] + + for size in two_size: + if size != min_size: + diff_half = (size - min_size) // 2 + new_slice.append(slice(diff_half, diff_half + min_size, 1)) + else: + new_slice.append(slice(0, min_size, 1)) + + image = image[tuple(new_slice)] + + return image From 36f5b04d2b4318d34a385f1cfa18549c25127a30 Mon Sep 17 00:00:00 2001 From: nastyafunkner Date: Wed, 20 Nov 2019 17:47:41 +0300 Subject: [PATCH 2/5] Practice #3 --- images/cars.jpg | Bin 0 -> 273873 bytes images/city.jpg | Bin 0 -> 995875 bytes images/cow.jpg | Bin 0 -> 145922 bytes images/cow2.jpg | Bin 0 -> 253287 bytes images/people.jpg | Bin 0 -> 9965 bytes images/plain.jpg | Bin 0 -> 43958 bytes samples/practice2_anastasia_funkner.py | 25 ++++-- src/ie_detector.py | 116 ++++++++++++++++++------- src/names_classes | 21 +++++ 9 files changed, 124 insertions(+), 38 deletions(-) create mode 100644 images/cars.jpg create mode 100644 images/city.jpg create mode 100644 images/cow.jpg create mode 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