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| | | import pandas as pd |
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| | | import fetch_data |
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| | | import generate_data |
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| | | from shapely import geometry |
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| | | |
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| | | card_mask = cv2.imread('data/mask.png') |
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| | | |
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| | |
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| | | Display the current state of the generator |
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| | | :return: none |
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| | | """ |
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| | | self.check_visibility() |
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| | | img_bg = cv2.resize(self.img_bg, (self.width, self.height)) |
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| | | |
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| | | for card in self.cards: |
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| | |
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| | | img_bg_crop = np.where(img_card_crop, img_card_crop, img_bg_crop) |
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| | | img_bg[bg_crop_y1:bg_crop_y2, bg_crop_x1:bg_crop_x2] = img_bg_crop |
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| | | |
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| | | #for extracted_object in card.objects: |
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| | | # for pt in extracted_object.key_pts: |
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| | | # cv2.circle(img_bg, card.coordinate_in_generator(pt[0], pt[1]), 2, (0, 0, 255), 2) |
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| | | # bounding_box = card.bb_in_generator(extracted_object.key_pts) |
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| | | # cv2.rectangle(img_bg, bounding_box[0], bounding_box[2], (0, 255, 0), 2) |
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| | | for ext_obj in card.objects: |
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| | | if ext_obj.visible: |
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| | | for pt in ext_obj.key_pts: |
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| | | cv2.circle(img_bg, card.coordinate_in_generator(pt[0], pt[1]), 2, (0, 0, 255), 2) |
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| | | bounding_box = card.bb_in_generator(ext_obj.key_pts) |
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| | | cv2.rectangle(img_bg, bounding_box[0], bounding_box[2], (0, 255, 0), 2) |
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| | | |
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| | | cv2.imshow('Result', img_bg) |
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| | | cv2.waitKey(0) |
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| | |
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| | | """ |
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| | | pass |
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| | | |
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| | | def check_visibility(self, visibility=0.5): |
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| | | """ |
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| | | Check whether if extracted objects in each card are visible in the current scenario, and update their status |
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| | | :param visibility: minimum ratio of the object's area that aren't covered by another card to be visible |
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| | | :return: none |
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| | | """ |
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| | | card_poly_list = [geometry.Polygon([card.coordinate_in_generator(0, 0), |
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| | | card.coordinate_in_generator(0, len(card.img)), |
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| | | card.coordinate_in_generator(len(card.img[0]), len(card.img)), |
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| | | card.coordinate_in_generator(len(card.img[0]), 0)]) for card in self.cards] |
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| | | |
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| | | # First card in the list is overlaid on the bottom of the card pile |
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| | | for i in range(len(self.cards)): |
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| | | card = self.cards[i] |
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| | | for ext_obj in card.objects: |
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| | | obj_poly = geometry.Polygon([card.coordinate_in_generator(pt[0], pt[1]) for pt in ext_obj.key_pts]) |
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| | | obj_area = obj_poly.area |
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| | | # Check if the other cards are blocking this object |
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| | | for card_poly in card_poly_list[i + 1:]: |
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| | | obj_poly = obj_poly.difference(card_poly) |
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| | | visible_area = obj_poly.area |
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| | | print("%s: %.1f visible" % (ext_obj.label, visible_area / obj_area)) |
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| | | ext_obj.visible = obj_area * visibility <= visible_area |
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| | | |
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| | | def export_training_data(self, out_dir): |
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| | | """ |
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| | | Export the generated training image along with the txt file for all bounding boxes |
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| | |
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| | | def __init__(self, label, key_pts): |
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| | | self.label = label |
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| | | self.key_pts = key_pts |
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| | | self.visible = False |
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| | | |
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| | | |
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| | | def main(): |
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| | |
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| | | if not is_planeswalker: |
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| | | card_pool = card_pool.append(card_info) |
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| | | a = 1 |
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| | | for i in [random.randrange(0, card_pool.shape[0] - 1, 1) for _ in range(24)]: |
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| | | for i in [random.randrange(0, card_pool.shape[0] - 1, 1) for _ in range(20)]: |
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| | | card_info = card_pool.iloc[i] |
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| | | img_name = '../usb/data/png/%s/%s_%s.png' % (card_info['set'], card_info['collector_number'], |
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| | | fetch_data.get_valid_filename(card_info['name'])) |
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