Added new test to validate video output with a webcam.

1 files changed, 61 insertions, 0 deletions

diff --git a/test-cli/test/helpers/detect.py b/test-cli/test/helpers/detect.py
new file mode 100644
index 0000000..193dabf
--- /dev/null
+++ b/test-cli/test/helpers/detect.py
@@ -0,0 +1,61 @@
+import cv2
+import numpy as np
+
+
+class Detect_Color(object):
+    oFrame = None
+    img_hsv = None
+    __red_lower1 = [0, 50, 20]
+    __red_upper1 = [5, 255, 255]
+    __red_lower2 = [175, 50, 20]
+    __red_upper2 = [180, 255, 255]
+    __blue_lower = [110, 50, 50]
+    __blue_upper = [130, 255, 255]
+    __green_lower = [36, 25, 25]
+    __green_upper = [86, 255, 255]
+
+    def __init__(self, frame):
+        self.oFrame = frame
+        self.__hist()
+
+    def __hist(self):
+        self.img_hsv = cv2.cvtColor(self.oFrame, cv2.COLOR_BGR2HSV)
+
+    def getRed(self):
+        return self.__detect_two_areas([0, 50, 20], [5, 255, 255], [175, 50, 20], [180, 255, 255])
+
+    def getBlue(self):
+        return self.__detect_one_area([110, 50, 50], [130, 255, 255])
+
+    def getGreen(self):
+        return self.__detect_one_area([36, 25, 25], [86, 255, 255])
+
+    def __detect_one_area(self, lower, upper):
+        a_lower = np.array(lower)
+        a_upper = np.array(upper)
+        c_mask = cv2.inRange(self.img_hsv, a_lower, a_upper)
+        croped = cv2.bitwise_and(self.oFrame, self.oFrame, mask=c_mask)
+        mean_v = cv2.mean(self.oFrame, mask=c_mask)
+        mean = {}
+        mean['R'] = mean_v[2]
+        mean['G'] = mean_v[1]
+        mean['B'] = mean_v[0]
+        count = cv2.countNonZero(c_mask)
+        return c_mask, croped, mean, count
+
+    def __detect_two_areas(self, lower1, upper1, lower2, upper2):
+        a1_lower = np.array(lower1)
+        a1_upper = np.array(upper1)
+        a2_lower = np.array(lower2)
+        a2_upper = np.array(upper2)
+        c_mask1 = cv2.inRange(self.img_hsv, a1_lower, a1_upper)
+        c_mask2 = cv2.inRange(self.img_hsv, a2_lower, a2_upper)
+        c_mask = cv2.bitwise_or(c_mask1, c_mask2)
+        croped = cv2.bitwise_and(self.oFrame, self.oFrame, mask=c_mask)
+        mean_v = cv2.mean(self.oFrame, mask=c_mask)
+        mean = {}
+        mean['R'] = mean_v[2]
+        mean['G'] = mean_v[1]
+        mean['B'] = mean_v[0]
+        count = cv2.countNonZero(c_mask)
+        return c_mask, croped, mean, count