~speedprog/mtg/mtg_card_detector.git

			@@ -1,17 +1,100 @@
			import random
			import math
			import cv2
			import numpy as np
			import imutils
			import pandas as pd
			import fetch_data
			import generate_data
			from shapely import geometry

			card_mask = cv2.imread('data/mask.png')


			class ImageGenerator:
			"""
			A template for generating a training image.
			"""
			def __init__(self, img_bg, cards):
			def __init__(self, img_bg, cards, width, height):
			"""
			:param img_bg: background (textile) image
			:param cards: list of Card objects
			:param width: width of the training image
			:param height: height of the training image
			"""
			self._img_bg = img_bg
			self._cards = cards
			self._img_result = None
			self.img_bg = img_bg
			self.cards = cards
			self.img_result = None
			self.width = width
			self.height = height
			pass

			def add_card(self, card, x=0, y=0, theta=0.0, scale=1.0):
			"""
			Add a card to this generator scenario.
			:param card: card to be added
			:param x: new X-coordinate for the centre of the card
			:param y: new Y-coordinate for the centre of the card
			:param theta: new angle for the card
			:param scale: new scale for the card
			:return: none
			"""
			self.cards.append(card)
			card.x = x
			card.y = y
			card.theta = theta
			card.scale = scale
			pass

			def display(self):
			"""
			Display the current state of the generator
			:return: none
			"""
			self.check_visibility()
			img_bg = cv2.resize(self.img_bg, (self.width, self.height))

			for card in self.cards:
			card_x = int(card.x + 0.5)
			card_y = int(card.y + 0.5)
			print(card_x, card_y, card.theta, card.scale)

			# Scale & rotate card image
			img_card = cv2.resize(card.img, (int(len(card.img[0]) * card.scale), int(len(card.img) * card.scale)))
			mask_scale = cv2.resize(card_mask, (int(len(card_mask[0]) * card.scale), int(len(card_mask) * card.scale)))
			img_mask = cv2.bitwise_and(img_card, mask_scale)
			img_rotate = imutils.rotate_bound(img_mask, card.theta / math.pi * 180)

			# Calculate the position of the card image in relation to the background
			# Crop the card image if it's out of boundary
			card_w = len(img_rotate[0])
			card_h = len(img_rotate)
			card_crop_x1 = max(0, card_w // 2 - card_x)
			card_crop_x2 = min(card_w, card_w // 2 + len(img_bg[0]) - card_x)
			card_crop_y1 = max(0, card_h // 2 - card_y)
			card_crop_y2 = min(card_h, card_h // 2 + len(img_bg) - card_y)
			img_card_crop = img_rotate[card_crop_y1:card_crop_y2, card_crop_x1:card_crop_x2]

			# Calculate the position of the corresponding area in the background
			bg_crop_x1 = max(0, card_x - (card_w // 2))
			bg_crop_x2 = min(len(img_bg[0]), int(card_x + (card_w / 2) + 0.5))
			bg_crop_y1 = max(0, card_y - (card_h // 2))
			bg_crop_y2 = min(len(img_bg), int(card_y + (card_h / 2) + 0.5))
			img_bg_crop = img_bg[bg_crop_y1:bg_crop_y2, bg_crop_x1:bg_crop_x2]

			# Override the background with the current card
			img_bg_crop = np.where(img_card_crop, img_card_crop, img_bg_crop)
			img_bg[bg_crop_y1:bg_crop_y2, bg_crop_x1:bg_crop_x2] = img_bg_crop

			for ext_obj in card.objects:
			if ext_obj.visible:
			for pt in ext_obj.key_pts:
			cv2.circle(img_bg, card.coordinate_in_generator(pt[0], pt[1]), 2, (0, 0, 255), 2)
			bounding_box = card.bb_in_generator(ext_obj.key_pts)
			cv2.rectangle(img_bg, bounding_box[0], bounding_box[2], (0, 255, 0), 2)

			cv2.imshow('Result', img_bg)
			cv2.waitKey(0)
			pass

			def generate_horizontal_span(self):
			@@ -35,6 +118,30 @@
			"""
			pass

			def check_visibility(self, visibility=0.5):
			"""
			Check whether if extracted objects in each card are visible in the current scenario, and update their status
			:param visibility: minimum ratio of the object's area that aren't covered by another card to be visible
			:return: none
			"""
			card_poly_list = [geometry.Polygon([card.coordinate_in_generator(0, 0),
			card.coordinate_in_generator(0, len(card.img)),
			card.coordinate_in_generator(len(card.img[0]), len(card.img)),
			card.coordinate_in_generator(len(card.img[0]), 0)]) for card in self.cards]

			# First card in the list is overlaid on the bottom of the card pile
			for i in range(len(self.cards)):
			card = self.cards[i]
			for ext_obj in card.objects:
			obj_poly = geometry.Polygon([card.coordinate_in_generator(pt[0], pt[1]) for pt in ext_obj.key_pts])
			obj_area = obj_poly.area
			# Check if the other cards are blocking this object
			for card_poly in card_poly_list[i + 1:]:
			obj_poly = obj_poly.difference(card_poly)
			visible_area = obj_poly.area
			print("%s: %.1f visible" % (ext_obj.label, visible_area / obj_area))
			ext_obj.visible = obj_area * visibility <= visible_area

			def export_training_data(self, out_dir):
			"""
			Export the generated training image along with the txt file for all bounding boxes
			@@ -47,7 +154,7 @@
			"""
			A class for storing required information about a card in relation to the ImageGenerator
			"""
			def __init__(self, img, card_info, objects, generator=None, x=None, y=None, theta=None):
			def __init__(self, img, card_info, objects, x=None, y=None, theta=None, scale=None):
			"""
			:param img: image of the card
			:param card_info: details like name, mana cost, type, set, etc
			@@ -56,57 +163,147 @@
			:param x: X-coordinate of the card's centre in relation to the generator
			:param y: Y-coordinate of the card's centre in relation to the generator
			:param theta: angle of rotation of the card in relation to the generator
			:param scale: scale of the card in the generator in relation to the original image
			"""
			self._img = img
			self._info = card_info
			self._objects = objects
			self._x = x
			self._y = y
			self._theta = theta
			self.img = img
			self.info = card_info
			self.objects = objects
			self.x = x
			self.y = y
			self.theta = theta
			self.scale = scale
			pass

			def bind_to_generator(self, generator, x=0, y=0, theta=0):
			"""
			Bind this card to an ImageGenerator object.
			:param generator: generator to be bound with
			:param x: new X-coordinate for the centre of the card
			:param y: new Y-coordinate for the centre of the card
			:param theta: new angle for the card
			:return: none
			"""
			pass

			def shift(self, x=None, y=None):
			def shift(self, x, y):
			"""
			Apply a X/Y translation on this image
			:param x: amount of X-translation. If range is given, translate by a random amount within that range
			:param y: amount of Y-translation. Refer to x when a range is given.
			:return: none
			"""
			if isinstance(x, tuple) or (isinstance(x, list) and len(x) == 2):
			self.x += random.uniform(x[0], x[1])
			else:
			self.x += x
			if isinstance(y, tuple) or (isinstance(y, list) and len(y) == 2):
			self.y += random.uniform(y[0], y[1])
			else:
			self.y += y
			pass

			def rotate(self, centre, theta=None):
			"""
			Apply a rotation on this image with a centre
			:param centre: coordinate of the centre of the rotation in relation to the centre of this card (self._x, self._y)
			:param theta: amount of rotation in radian. If a range is given, rotate by a random amount within that range
			:param centre: coordinate of the centre of the rotation in relation to the centre of this card
			:param theta: amount of rotation in radian (clockwise). If a range is given, rotate by a random amount within
			that range
			:return: none
			"""
			if isinstance(theta, tuple) or (isinstance(theta, list) and len(theta) == 2):
			theta = random.uniform(theta[0], theta[1])

			# Rotation math
			self.x -= -centre[1] * math.sin(theta) + centre[0] * math.cos(theta)
			self.y -= centre[1] * math.cos(theta) + centre[0] * math.sin(theta)

			# Offset for the coordinate translation
			self.x += centre[0]
			self.y += centre[1]

			self.theta += theta
			pass

			def coordinate_in_generator(self, x, y):
			"""
			Converting coordinate within the card into the coordinate in the generator it is associated with
			:param x: x coordinate within the card
			:param y: y coordinate within the card
			:return: (x, y) coordinate in the generator
			"""
			# Relative distance in X & Y axis, if the centre of the card is at the origin (0, 0)
			rel_x = x - len(self.img[0]) // 2
			rel_y = y - len(self.img) // 2

			# Scaling
			rel_x *= self.scale
			rel_y *= self.scale

			# Rotation
			rot_x = rel_x - rel_y * math.sin(self.theta) + rel_x * math.cos(self.theta)
			rot_y = rel_y + rel_y * math.cos(self.theta) + rel_x * math.sin(self.theta)

			# Negate offset
			rot_x -= rel_x
			rot_y -= rel_y

			# Shift
			gen_x = rot_x + self.x
			gen_y = rot_y + self.y

			return int(gen_x), int(gen_y)

			def bb_in_generator(self, key_pts):
			"""
			Convert a keypoints of bounding box in card into the coordinate in the generator
			:param key_pts: keypoints of the bounding box
			:return: bounding box represented by 4 points in the generator
			"""
			x1 = -math.inf
			x2 = math.inf
			y1 = -math.inf
			y2 = math.inf
			for key_pt in key_pts:
			coord_in_gen = self.coordinate_in_generator(key_pt[0], key_pt[1])
			x1 = max(x1, coord_in_gen[0])
			x2 = min(x2, coord_in_gen[0])
			y1 = max(y1, coord_in_gen[1])
			y2 = min(y2, coord_in_gen[1])
			return [(x1, y1), (x2, y1), (x2, y2), (x1, y2)]


			class ExtractedObject:
			"""
			Simple struct to hold information about an extracted object
			"""
			def __init__(self, label, key_pts):
			self._label = label
			self._key_pts = key_pts
			self.label = label
			self.key_pts = key_pts
			self.visible = False


			def main():
			random.seed()
			img_bg = cv2.imread('data/frilly_0007.jpg')
			generator = ImageGenerator(img_bg, [], 1440, 960)
			card_pool = pd.DataFrame()
			for set_name in fetch_data.all_set_list:
			df = fetch_data.load_all_cards_text('data/csv/%s.csv' % set_name)
			card_info = df.iloc[random.randint(0, df.shape[0] - 1)]
			# Currently ignoring planeswalker cards due to their different card layout
			is_planeswalker = 'Planeswalker' in card_info['type_line']
			if not is_planeswalker:
			card_pool = card_pool.append(card_info)
			a = 1
			for i in [random.randrange(0, card_pool.shape[0] - 1, 1) for _ in range(20)]:
			card_info = card_pool.iloc[i]
			img_name = '../usb/data/png/%s/%s_%s.png' % (card_info['set'], card_info['collector_number'],
			fetch_data.get_valid_filename(card_info['name']))
			print(img_name)
			card_img = cv2.imread(img_name)
			if card_img is None:
			fetch_data.fetch_card_image(card_info, out_dir='../usb/data/png/%s' % card_info['set'])
			card_img = cv2.imread(img_name)
			detected_object_list = generate_data.apply_bounding_box(card_img, card_info)
			card = Card(card_img, card_info, detected_object_list)

			generator.add_card(card, x=random.uniform(200, generator.width - 200),
			y=random.uniform(200, generator.height - 200), theta=random.uniform(-math.pi, math.pi), scale=0.5)
			#card.shift([-100, 100], [-100, 100])
			#card.rotate((0, 0), [-math.pi / 4, math.pi / 4])
			a += 1
			generator.display()
			pass


			if __name__ == '__main__':
			main()
			main()