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Author: AhmetFurkanDEMIR

Diff for: OpenCV_GoogleDino.py

@@ -0,0 +1,89 @@
+import pyautogui
+import cv2
+import mss
+import numpy as np
+import threading
+import time
+
+monitor = {'top': 0, 'left': 0, 'width': 1366, 'height': 768}
+sct = mss.mss()
+
+color_space_up = np.array([90, 90, 90], np.uint8)
+color_space_dow = np.array([70, 70, 70], np.uint8)
+
+color_black = np.array([0, 0, 0], np.uint8)
+color_white = np.array([255, 255, 255], np.uint8)
+
+fourcc = cv2.VideoWriter_fourcc(*'XVID')
+out = cv2.VideoWriter('output.avi',fourcc, 80, (1366,768))
+
+
+def thre_space():
+
+	pyautogui.keyDown('space')
+	time.sleep(0.3)
+	pyautogui.keyUp('space')
+
+
+while True:
+
+	img = np.array(sct.grab(monitor))
+	frame = cv2.cvtColor(img, cv2.COLOR_BGR2RGB)
+
+	cv2.rectangle(frame, pt1=(480,190), pt2=(560,240), color=(0,0,255), thickness=3)
+	squ0 = frame[190:240, 480:560, :]
+
+	cv2.rectangle(frame, pt1=(110,214), pt2=(176,338), color=(0,0,255), thickness=3)
+	squ1 = frame[214:338, 110:176, :]
+
+
+	mask = cv2.inRange(squ0, color_space_dow, color_space_up)
+	kernal = np.ones((5, 5), "uint8")
+	black_mask0 = cv2.dilate(mask, kernal)
+	res_red = cv2.bitwise_and(squ0, squ0, mask = black_mask0)
+	contours, hierarchy = cv2.findContours(black_mask0, cv2.RETR_TREE, cv2.CHAIN_APPROX_SIMPLE)
+
+
+	for pic, contour in enumerate(contours):
+		area = cv2.contourArea(contour)
+		if(area > 300):
+			a = threading.Thread(target=thre_space)
+			a.start()
+
+	mask = cv2.inRange(squ1, color_black, color_black)
+	kernal = np.ones((5, 5), "uint8")
+	black_mask0 = cv2.dilate(mask, kernal)
+	res_red = cv2.bitwise_and(squ1, squ1, mask = black_mask0)
+	contours, hierarchy = cv2.findContours(black_mask0, cv2.RETR_TREE, cv2.CHAIN_APPROX_SIMPLE)
+
+
+	for pic, contour in enumerate(contours):
+		area = cv2.contourArea(contour)
+		if(area > 300):	
+			color_space = np.array([172, 172, 172], np.uint8)
+
+			color_space_up = np.array([185, 185, 185], np.uint8)
+			color_space_dow = np.array([165, 165, 165], np.uint8)
+
+
+	mask = cv2.inRange(squ1, color_white, color_white)
+	kernal = np.ones((5, 5), "uint8")
+	black_mask0 = cv2.dilate(mask, kernal)
+	res_red = cv2.bitwise_and(squ1, squ1, mask = black_mask0)
+	contours, hierarchy = cv2.findContours(black_mask0, cv2.RETR_TREE, cv2.CHAIN_APPROX_SIMPLE)
+
+
+	for pic, contour in enumerate(contours):
+		area = cv2.contourArea(contour)
+		if(area > 300):	
+			color_space_up = np.array([90, 90, 90], np.uint8)
+			color_space_dow = np.array([70, 70, 70], np.uint8)
+
+
+
+	frame = cv2.cvtColor(frame, cv2.COLOR_BGR2RGB)
+	out.write(frame)
+	if cv2.waitKey(1) & 0xFF == ord('q'):
+		break
+
+out.release()