commit

Author: manthan89-py

Readme.md

@@ -30,6 +30,10 @@
 * template_matching_opencv.py
 * hough_line_transform_opencv.py
 * probabilistic_hough_line_transform.py
+* lande_detection_opencv.py
+* circle_detection_using_hough_transform.py
+* face_detection_opencv.py
+
 
 ## Helpful Documentations⭐:
 * OpenCV : https://docs.opencv.org/master/

circle_detection_using_hough_transform.py

@@ -0,0 +1,20 @@
+import numpy as np
+import cv2 as cv
+
+# img = cv.imread('test_images/shapes.jpg')
+img = cv.imread('test_images/smarites.jpg')
+output = img.copy()
+
+gray = cv.cvtColor(img, cv.COLOR_BGR2GRAY)
+gray = cv.medianBlur(gray, 5)
+# circles = cv.HoughCircles(gray, cv.HOUGH_GRADIENT, 1, 20, param1=50, param2=30, minRadius=0, maxRadius=0)
+circles = cv.HoughCircles(gray, cv.HOUGH_GRADIENT, 1, 60, param1=50, param2=30, minRadius=0, maxRadius=70)
+
+detected_circles = np.uint16(np.around(circles))
+for (x, y, r) in detected_circles[0, :]:
+    cv.circle(output, (x, y), r, (0,255,0), 3)
+    cv.circle(output, (x, y), 2, (0, 255, 255), 3)
+
+cv.imshow('output', output)
+cv.waitKey(0)
+cv.destroyAllWindows()

face_detection_opencv.py

@@ -0,0 +1,47 @@
+import cv2
+# object detection based on Haar cascade classifier
+
+#image face detection
+# face_cascade = cv2.CascadeClassifier('haarcascade_frontalface_default.xml')
+# img = cv2.imread('test_images/test.jpg')
+#
+#
+# gray = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)
+# faces = face_cascade.detectMultiScale(gray, 1.1, 4)
+#
+# for (x, y, w, h) in faces:
+#     cv2.rectangle(img, (x, y), (x+w, y+h), (255,0,0),3)
+#
+#
+# cv2.imshow('img', img)
+# cv2.waitKey(0)
+#
+# cv2.destroyAllWindows()
+
+
+
+# video face detection
+
+## You have to download haarcascade_frontalface_default from internet
+
+face_cascade = cv2.CascadeClassifier('haarcascade_frontalface_default.xml')
+# img = cv2.imread('test_images/test.jpg')
+cap = cv2.VideoCapture(0) 
+
+while cap.isOpened():
+    _, img = cap.read()
+
+    gray = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)
+    faces = face_cascade.detectMultiScale(gray, 1.1, 4)
+
+    for (x, y, w, h) in faces:
+        cv2.rectangle(img, (x, y), (x+w, y+h), (255,0,0),3)
+
+
+    cv2.imshow('img', img)
+    if cv2.waitKey(1) & 0xff == ord('q'):
+        break
+
+cv2.destroyAllWindows()
+
+cap.release()

lane_detection_opencv.py

@@ -0,0 +1,69 @@
+import matplotlib.pyplot as plt
+import cv2
+import numpy as np
+
+def region_of_interest(img, vertices):
+    mask = np.zeros_like(img)
+    # channel_count = img.shape[2]
+    match_mask_color = 255  #, ) * channel_count
+    cv2.fillPoly(mask, vertices, match_mask_color)
+    masked_image = cv2.bitwise_and(img, mask)
+    return masked_image
+
+def draw_the_lines(img, lines):
+    img = np.copy(img)
+    blank_image = np.zeros((img.shape[0], img.shape[1], 3), dtype=np.uint8)
+
+    for line in lines:
+        for x1, y1, x2, y2 in line:
+            cv2.line(blank_image, (x1, y1), (x2, y2), (0,255,0), thickness=3)
+
+
+    img = cv2.addWeighted(img, 0.8, blank_image,  1, 0.0)
+    return img
+
+# image = cv2.imread('road.jpg')
+# image = cv2.cvtColor(image, cv2.COLOR_BGR2RGB)
+
+def process(image):
+
+    # print(image.shape)
+    height = image.shape[0]
+    width = image.shape[1]
+
+    region_of_interest_vertices = [
+
+        (0, height),
+        (width/2, height/2),
+        (width,height)
+
+        # (120, height),
+        # (width / 2, height / 2),
+        # (width, 180)
+    ]
+
+    gray_image = cv2.cvtColor(image, cv2.COLOR_RGB2GRAY)
+    canny_image = cv2.Canny(gray_image, 100, 120)
+
+    cropped_image = region_of_interest(canny_image,
+            np.array([region_of_interest_vertices], np.int32))
+    lines = cv2.HoughLinesP(cropped_image, rho=2, theta=np.pi/60, threshold=50, lines=np.array([]), minLineLength=40, maxLineGap=100)
+
+    image_with_lines = draw_the_lines(image, lines)
+    if lines is None:
+        image_with_lines = image
+
+    return image_with_lines
+
+
+cap = cv2.VideoCapture('test_images/test_video.mp4')
+
+while(cap.isOpened()):
+    ret, frame = cap.read()
+    frame = process(frame)
+    cv2.imshow('frame',frame)
+    if cv2.waitKeyEx(1) & 0xff == ord('q'):
+        break
+
+cap.release()
+cv2.destroyAllWindows()