> For the complete documentation index, see [llms.txt](https://docs.aic-eec.com/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://docs.aic-eec.com/artificial-intelligence-ai/basic-image-processing/computer-vision-for-python/lab-3-case-study/untitled.md).

# Color detection & tracking

**inRange**

```
$ cv2.inRange(image, lower, upper)
```

**Parameter:**

* image => ภาพที่ต้องการนำมาใช้
* lower => ค่าสีต่ำสุดที่ต้องการ โดยเขียนในลักษณะ tuple BGR
* upper => ค่าสีสูงสุดที่ต้องการ โดยเขียนในลักษณะ tuple BGR

**Example:**

```
import numpy as np
import cv2

image = cv2.imread("path/your/image.jpg")

colors = [
	([17, 15, 100], [50, 56, 200]),
	([86, 31, 4], [220, 88, 50]),
	([25, 146, 190], [62, 174, 250]),
	([103, 86, 65], [145, 133, 128])
]


for (lower, upper) in colors:

	lower = np.array(lower, dtype = "uint8")
	upper = np.array(upper, dtype = "uint8")

	mask = cv2.inRange(image, lower, upper)
	output = cv2.bitwise_and(image, image, mask = mask)
	
	cv2.imshow("images", np.hstack([image, output]))
	cv2.waitKey(0)
```

### tracking

     tracking จะเป็นเทคนิคที่ใช้ในการติดตามวัตถุที่อยู่บนภาพวิดีโอหรือการแสดงภาพแบบ Real-time โดยในหัวข้อนี้จะเป็นการติดตามวัตถุที่มีสีตามที่ผู้ใช้กำหนด

* รับภาพที่เป็นวิดีโอหรือภาพจากกล้อง webcam
* กำหนดค่าสีที่ต้องการใช้งาน
* color detection
* contour

**Example:**

```
import imutils
import cv2

camera = cv2.VideoCapture(0)

colorRanges = [
	((29, 86, 6), (64, 255, 255), "green"),
	((57, 68, 0), (151, 255, 255), "blue")]

while True:

	(grabbed, frame) = camera.read()

	frame = imutils.resize(frame, width=600)
	blurred = cv2.GaussianBlur(frame, (11, 11), 0)
	
	hsv = cv2.cvtColor(frame, cv2.COLOR_BGR2HSV)

	for (lower, upper, colorName) in colorRanges:

		mask = cv2.inRange(hsv, lower, upper)
		mask = cv2.erode(mask, None, iterations=2)
		mask = cv2.dilate(mask, None, iterations=2)

		cnts = cv2.findContours(mask.copy(), cv2.RETR_EXTERNAL,
			cv2.CHAIN_APPROX_SIMPLE)
		cnts = imutils.grab_contours(cnts)

		if len(cnts) > 0:

			c = max(cnts, key=cv2.contourArea)
			((x, y), radius) = cv2.minEnclosingCircle(c)
			M = cv2.moments(c)
			(cX, cY) = (int(M["m10"] / M["m00"]), int(M["m01"] / M["m00"]))

			if radius > 10:
				cv2.circle(frame, (int(x), int(y)), int(radius), (0, 255, 255), 2)
				cv2.putText(frame, colorName, (cX, cY), cv2.FONT_HERSHEY_SIMPLEX,
					1.0, (0, 255, 255), 2)


	cv2.imshow("Frame", frame)
	key = cv2.waitKey(1) & 0xFF

	if key == ord("q"):
		break

camera.release()
cv2.destroyAllWindows()
```


---

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