import cv2
import numpy as np
import imutils as im

from util import bbox_round, image_crop, to_rect, bbox_add_position, bbox_center

IMG_SCALE_UP = 1
IMG_ROTATE = 0

COLOR_TRACKER = (0, 255, 0)
COLOR_TRACKER_EXT = (0, 255, 255)
COLOR_MATCHER = (0, 0, 255)
COLOR_TEMPLATE = (255, 0, 0)
TEMPLATE_MATCH_OVERLAP = 0

CONSOLE_DEBUG = False
IMAGE_DEBUG = False


class Corner:
	def __init__(self, reference: np.array, bbox: np.array, name: str = 'Corner'):
		self.ref = {'image': reference, 'bbox': bbox, 'offset': (0, 0)}
		self.name = name
		self._path = []
		self.line_from = None
		self.first_frame = True

	def _debug(self, _image, matcher_res, matcher_start_x, matcher_start_y, template_scaled, crop_scaled):
		template_img = self.ref['image']
		offset = self.ref['offset']

		(min_val, max_val, min_loc, max_loc) = cv2.minMaxLoc(matcher_res)

		self._print(f"(min_val, max_val, min_loc, max_loc): {(min_val, max_val, min_loc, max_loc)}")
		self._print(f"matcher_start   : {(matcher_start_x, matcher_start_y)}")
		self._print(f"matcher_res     : {matcher_res.shape}")
		self._print(f"crop            : {_image.shape}")
		self._print(f"crop_scaled     : {crop_scaled.shape}")
		self._print(f"template        : {template_img.shape}")
		self._print(f"template_scaled : {template_scaled.shape}")
		self._print(f"offset 		  : {offset}")

		if IMAGE_DEBUG:
			matcher_bbox_local = (matcher_start_x, matcher_start_y, template_img.shape[1], template_img.shape[0])
			matcher_crop = image_crop(_image, matcher_bbox_local)
			cv2.imshow(f"{self.name}: Matcher res", matcher_res)
			cv2.imshow(f"{self.name}: Matcher view", matcher_crop)

	def _print(self, s):
		if CONSOLE_DEBUG:
			print(f"{self.name}: {s}")

	def process(self, _image: np.array):
		_image_anno = _image.copy()
		crop_scaled = im.resize(_image, IMG_SCALE_UP * _image.shape[1], IMG_SCALE_UP * _image.shape[0])
		template = self.ref['image']
		bb_template = self.ref['bbox']

		# Resize template
		template_scaled = im.resize(template, IMG_SCALE_UP * template.shape[0], IMG_SCALE_UP * template.shape[1])
		# Match
		matcher_res = cv2.matchTemplate(crop_scaled, template_scaled, cv2.TM_CCOEFF_NORMED)
		(min_val, max_val, min_loc, max_loc) = cv2.minMaxLoc(matcher_res)

		# Get matcher coord
		matcher_start_x = max_loc[0]/IMG_SCALE_UP
		matcher_start_y = max_loc[1]/IMG_SCALE_UP

		# Store offset at first frame
		if self.first_frame:
			self.first_frame = False
			offset_x = matcher_start_x - bb_template[0]
			offset_y = matcher_start_y - bb_template[1]
			self.ref['offset'] = (offset_x, offset_y)

		# Compensate offset
		matcher_start_x -= self.ref['offset'][0]
		matcher_start_y -= self.ref['offset'][1]

		matcher_bbox_local = (matcher_start_x, matcher_start_y, template.shape[1], template.shape[0])

		self._debug(_image_anno, matcher_res, matcher_start_x, matcher_start_y, template_scaled, crop_scaled)

		return matcher_bbox_local, matcher_res

	def path_add(self, point):
		if len(self.path) > 200:
			return
		if self.line_from is not None:
			self._path.append({'from': self.line_from, 'to': point})
		self.line_from = point

	@property
	def path(self):
		return self._path


class CornerTracker:
	def __init__(self, color=(0, 255, 0), name: str = 'CornerTracker'):
		self.color = color
		self.name = name
		self.tracking_ref_bb = None
		self.tracking_ref_img = None
		self.tracking_ref_gray_img = None
		self.matching_tpl_bb = None
		self.matching_tpl_img = None
		self.tracking_bb = None
		self.tracking_img = None
		self.tracker = cv2.TrackerKCF.create()
		self.corner_ref = None
		self.corner_matcher_list = []

	def _print(self, s):
		if CONSOLE_DEBUG:
			print(f"{self.name}: {s}")

	def _debug(self, _image_anno, tracking_anno, matcher_bbox_local):
		matcher_bbox = bbox_round(bbox_add_position(matcher_bbox_local, self.tracking_bb))

		template_top_left, template_bottom_right = to_rect(self.matching_tpl_bb)
		cv2.rectangle(tracking_anno, template_top_left, template_bottom_right, COLOR_TEMPLATE, 1)

		matcher_top_left_local, matcher_bottom_right_local = to_rect(bbox_round(matcher_bbox_local))
		cv2.rectangle(tracking_anno, matcher_top_left_local, matcher_bottom_right_local, COLOR_MATCHER, 1)

		matcher_rect = to_rect(matcher_bbox)
		cv2.rectangle(_image_anno, matcher_rect[0], matcher_rect[1], COLOR_MATCHER, 1)

		tracker_rect = to_rect(bbox_round(self.tracking_bb))
		cv2.rectangle(_image_anno, tracker_rect[0], tracker_rect[1], self.color, 1)

	def init_reference_frame(self, _image: np.array):
		print(f"Select tracking object")
		bb = cv2.selectROI("Tracker Reference", _image, False)
		cv2.destroyWindow("Tracker Reference")
		if bbox_center(bb) == (0, 0):
			return False

		self.tracking_ref_bb = bb
		self.tracking_ref_img = image_crop(_image, self.tracking_ref_bb)
		self.tracking_ref_gray_img = cv2.cvtColor(self.tracking_ref_img, cv2.COLOR_BGR2GRAY)
		self.corner_matcher_list = []

		corner_list = []
		count = 1
		while True:
			print(f"Add Corner {count}")
			bb = cv2.selectROI("Matcher Reference", self.tracking_ref_img, fromCenter=True, showCrosshair=True)
			if bbox_center(bb) == (0, 0):
				break

			self.matching_tpl_bb = bb
			self.matching_tpl_img = image_crop(self.tracking_ref_gray_img.copy(), self.matching_tpl_bb)
			self.corner_matcher_list.append(Corner(self.matching_tpl_img, self.matching_tpl_bb, name=f"Corner-{count}"))
			corner_list.append(bbox_center(bbox_add_position(self.matching_tpl_bb, self.tracking_ref_bb)))

			print(f"Corner {count} added")
			print(f"Press any key to add another corner or ESC to continue")

			count += 1

		cv2.destroyWindow("Matcher Reference")
		print(f"Added {count} corners")

		if len(corner_list) == 0:
			return False

		# Initialize tracker with first frame and bounding box
		self.tracker.init(_image, self.tracking_ref_bb)

		# Refine initial corners and store them as reference
		self.corner_ref = self._corner_refine(cv2.cvtColor(_image, cv2.COLOR_BGR2GRAY), corners=corner_list)

		return True

	def process(self, _image: np.array, _image_anno: np.array):
		if self.tracker is None:
			raise Exception(f"{self.name}: Call init_reference_frame() first")

		# Update tracker
		_ok, tracking_bb = self.tracker.update(_image)
		if not _ok:
			return None

		tracking_img = image_crop(_image.copy(), tracking_bb)
		tracking_img = cv2.cvtColor(tracking_img, cv2.COLOR_BGR2GRAY)
		self.tracking_img = cv2.GaussianBlur(tracking_img, (9, 9), 0)
		self.tracking_bb = tracking_bb

		return self._match(_image, _image_anno)

	def _match(self, _image: np.array, _image_anno: np.array):
		tracking_anno = self.tracking_img.copy()
		corners_raw = []
		for _ct in self.corner_matcher_list:
			matcher_bbox_local, matcher = _ct.process(self.tracking_img)
			matcher_bbox = bbox_add_position(matcher_bbox_local, self.tracking_bb)

			# Draw path
			corner = bbox_center(matcher_bbox)
			corners_raw.append(corner)

			self._debug(_image_anno, tracking_anno, matcher_bbox_local)

		# refine corners
		corners_refined = self._corner_refine(cv2.cvtColor(_image, cv2.COLOR_BGR2GRAY), corners_raw)

		# store refined corners
		_i = 0
		for corner in corners_refined:
			_ct = self.corner_matcher_list[_i]
			_ct.path_add(corner)
			_i += 1

		# draw path
		for _ct in self.corner_matcher_list:
			for p in _ct.path:
				cv2.line(_image_anno, bbox_round(p['from']), bbox_round(p['to']), (0, 0, 255), 1)

		distances = []
		for _i in range(0, corners_refined.shape[0]):
			distances.append((corners_refined[_i] - self.corner_ref[_i]))

		_mean_distance = np.mean(distances, axis=0)

		# show refined corners
		for _i in range(0, corners_refined.shape[0]):
			self._print(f" -- Corner Reference [{i}] {self.corner_ref[_i]}")
			self._print(f" -- Corner coarse    [{i}] {corners_raw[_i]}")
			self._print(f" -- Corner fine      [{i}] {corners_refined[_i]}")
			self._print(f" -- Corner distance  [{i}] {corners_refined[_i] - self.corner_ref[_i]}")
			cv2.circle(_image_anno, (int(corners_refined[_i, 0]), int(corners_refined[_i, 1])), 4, (0, 255, 0))

		if IMAGE_DEBUG:
			cv2.imshow(f"{self.name}: Tracker: ", self.tracking_img)

		return _mean_distance

	@staticmethod
	def _corner_refine(src_gray, corners: np.array):
		# convert from (n, 2) to (n, 1, 2)
		corners_original = []
		for corner in corners:
			corners_original.append([corner])

		corners_original = np.array(corners_original, dtype=np.float32)

		# Set the needed parameters to find the refined corners
		win_size = (5, 5)
		zero_zone = (-1, -1)
		criteria = (cv2.TERM_CRITERIA_EPS + cv2.TermCriteria_COUNT, 40, 0.001)

		# Calculate the refined corner locations
		corners_refined = cv2.cornerSubPix(src_gray, corners_original.copy(), win_size, zero_zone, criteria)

		# Write them down
		corner_result = []
		for _i in range(corners_original.shape[0]):
			corner = (corners_refined[_i, 0, 0], corners_refined[_i, 0, 1])
			corner_result.append(corner)

		return np.array(corner_result)


if __name__ == '__main__':
	colors = [(255, 0, 0), (0, 255, 0), (0, 0, 255), (255, 0, 255), (0, 255, 255), (255, 255, 255)]
	video = cv2.VideoCapture('./data/spindle_multi_black/%04d.png')
	tracker_count = 0
	tracker_list = []
	if video.isOpened():
		# Read first frame.
		ok, image = video.read()
		if ok:
			for tracker_count in range(0, 6):
				select_window = image.copy()
				print(f"Add tracker #{tracker_count}")
				ct = CornerTracker(colors[tracker_count], name=f"Tracker-{tracker_count}")
				ok = ct.init_reference_frame(select_window)
				if ok:
					tracker_list.append(ct)
					print(f"Number of active tracker: {len(tracker_list)}")
				else:
					break

		else:
			print('Cannot read video file')

		key_wait = -1
		while True:
			# Start timer
			timer = cv2.getTickCount()
			# Read a new frame
			ok, image = video.read()
			if ok:
				image_anno = image.copy()
				i = 0
				for ct in tracker_list:
					mean_distance = ct.process(image, image_anno)
					if mean_distance is not None:
						cv2.putText(image_anno, f"Distance [{i}] : ({mean_distance[0]:+05.2f}, {mean_distance[1]:+05.2f})",
								(20, 20 + 20 * i), cv2.FONT_HERSHEY_SIMPLEX, 0.5, ct.color, 1)
					i += 1

				# Calculate Frames per second (FPS)
				fps = cv2.getTickFrequency() / (cv2.getTickCount() - timer)
				# Display FPS on frame
				cv2.putText(image_anno, "FPS : " + str(int(fps)), (20, image_anno.shape[0] - 20),
							cv2.FONT_HERSHEY_SIMPLEX, 0.5, (50, 170, 50), 1)

				cv2.imshow(f"Image Anno", image_anno)
			else:
				video.set(cv2.CAP_PROP_POS_FRAMES, 0)
				continue

			# Exit if ESC pressed
			k = cv2.waitKey(key_wait) & 0xff
			if k == 27:
				break
			if k == ord(' '):
				if key_wait == -1:
					key_wait = 1
				else:
					key_wait = -1

	else:
		print('Cannot open video file')