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76 changes: 40 additions & 36 deletions Camera_Color_Detection_and_Tracking_with_OpenCV.py
View file
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Original file line number Diff line number Diff line change
Expand Up @@ -8,12 +8,15 @@
cap.set(4, frameHeight)

def emptyFunction(a):
threshold1 = cv2.getTrackbarPos("Threshold1", "Parameters")
threshold2 = cv2.getTrackbarPos("Threshold2", "Parameters")
area = cv2.getTrackbarPos("Area", "Parameters")
print("Threshold1:", threshold1)
print("Threshold2:", threshold2)
print("Area:", area)
hMin = cv2.getTrackbarPos("HUE Min", "HSV")
hMax = cv2.getTrackbarPos("HUE Max", "HSV")
sMin = cv2.getTrackbarPos("SAT Min", "HSV")
sMax = cv2.getTrackbarPos("SAT Max", "HSV")
vMin = cv2.getTrackbarPos("VALUE Min", "HSV")
vMax = cv2.getTrackbarPos("VALUE Max", "HSV")
print("HUE Min:", hMin, "HUE Max:", hMax)
print("SAT Min:", sMin, "SAT Max:", sMax)
print("VALUE Min:", vMin, "VALUE Max:", vMax)

cv2.namedWindow("HSV")
cv2.resizeWindow("HSV", 640, 240)
Expand All @@ -24,33 +27,34 @@ def emptyFunction(a):
cv2.createTrackbar("VALUE Min", "HSV", 0, 255, emptyFunction)
cv2.createTrackbar("VALUE Max", "HSV", 255, 255, emptyFunction)

while True:
ret, frame = cap.read()

if not ret:
print("Failed to capture frame from the camera.")
break

imgHsv = cv2.cvtColor(frame, cv2.COLOR_BGR2HSV)

hMin = cv2.getTrackbarPos("HUE Min", "HSV")
hMax = cv2.getTrackbarPos("HUE Max", "HSV")
sMin = cv2.getTrackbarPos("SAT Min", "HSV")
sMax = cv2.getTrackbarPos("SAT Max", "HSV")
vMin = cv2.getTrackbarPos("VALUE Min", "HSV")
vMax = cv2.getTrackbarPos("VALUE Max", "HSV")

lower = np.array([hMin, sMin, vMin])
upper = np.array([hMax, sMax, vMax])
mask = cv2.inRange(imgHsv, lower, upper)
result = cv2.bitwise_and(frame, frame, mask=mask)

mask = cv2.cvtColor(mask, cv2.COLOR_GRAY2BGR)
hStack = np.hstack([frame, mask, result])
cv2.imshow('Horizontal Stacking', hStack)

if cv2.waitKey(1) & 0xFF == ord('q'):
break

cap.release()
cv2.destroyAllWindows()
try:
while True:
ret, frame = cap.read()

if not ret:
print("Failed to capture frame from the camera.")
break

imgHsv = cv2.cvtColor(frame, cv2.COLOR_BGR2HSV)

hMin = cv2.getTrackbarPos("HUE Min", "HSV")
hMax = cv2.getTrackbarPos("HUE Max", "HSV")
sMin = cv2.getTrackbarPos("SAT Min", "HSV")
sMax = cv2.getTrackbarPos("SAT Max", "HSV")
vMin = cv2.getTrackbarPos("VALUE Min", "HSV")
vMax = cv2.getTrackbarPos("VALUE Max", "HSV")

lower = np.array([hMin, sMin, vMin])
upper = np.array([hMax, sMax, vMax])
mask = cv2.inRange(imgHsv, lower, upper)
result = cv2.bitwise_and(frame, frame, mask=mask)

mask = cv2.cvtColor(mask, cv2.COLOR_GRAY2BGR)
hStack = np.hstack([frame, mask, result])
cv2.imshow('Horizontal Stacking', hStack)

if cv2.waitKey(1) & 0xFF == ord('q'):
break
finally:
cap.release()
cv2.destroyAllWindows()
38 changes: 23 additions & 15 deletions Real-time_Object_Detection_and_Tracking.py
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -70,21 +70,29 @@ def getContours(img,imgContour):
cv2.putText(imgContour, "Points: " + str(len(approx)), (x + w + 20, y + 20), cv2.FONT_HERSHEY_COMPLEX, .7, (0, 255, 0), 2)
cv2.putText(imgContour, "Area: " + str(int(area)), (x + w + 20, y + 45), cv2.FONT_HERSHEY_COMPLEX, 0.7, (0, 255, 0), 2)

while True:
success, img = cap.read()
imgContour = img.copy()
imgBlur = cv2.GaussianBlur(img, (7, 7), 1)
imgGray = cv2.cvtColor(imgBlur, cv2.COLOR_BGR2GRAY)
threshold1 = cv2.getTrackbarPos("Threshold1", "Parameters")
threshold2 = cv2.getTrackbarPos("Threshold2", "Parameters")
imgCanny = cv2.Canny(imgGray,threshold1,threshold2)
kernel = np.ones((5, 5))
imgDil = cv2.dilate(imgCanny, kernel, iterations=1)
getContours(imgDil,imgContour)
imgStack = stackImages(0.8,([img,imgCanny], [imgDil,imgContour]))
cv2.imshow("Result", imgStack)
if cv2.waitKey(1) & 0xFF == ord('q'):
break
try:
while True:
success, img = cap.read()
if not success:
print("Failed to capture image")
break

imgContour = img.copy()
imgBlur = cv2.GaussianBlur(img, (7, 7), 1)
imgGray = cv2.cvtColor(imgBlur, cv2.COLOR_BGR2GRAY)
threshold1 = cv2.getTrackbarPos("Threshold1", "Parameters")
threshold2 = cv2.getTrackbarPos("Threshold2", "Parameters")
imgCanny = cv2.Canny(imgGray,threshold1,threshold2)
kernel = np.ones((5, 5))
imgDil = cv2.dilate(imgCanny, kernel, iterations=1)
getContours(imgDil,imgContour)
imgStack = stackImages(0.8,([img,imgCanny], [imgDil,imgContour]))
cv2.imshow("Result", imgStack)
if cv2.waitKey(1) & 0xFF == ord('q'):
break
finally:
cap.release()
cv2.destroyAllWindows()



Expand Down
136 changes: 70 additions & 66 deletions Real-time_Object_Tracking.py
View file
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Original file line number Diff line number Diff line change
Expand Up @@ -3,75 +3,79 @@
import cv2
import time

# Create a tracker object
tracker = cv2.TrackerKCF_create()
# Create a tracker object (handle OpenCV version compatibility)
try:
tracker = cv2.TrackerKCF_create()
except AttributeError:
tracker = cv2.legacy.TrackerKCF_create()

# Open the video capture
cap = cv2.VideoCapture(0)

# Read the first frame from the video
success, frame = cap.read()
if not success:
print("Failed to read video")
exit()

# Select the region of interest (ROI) for tracking
bbox = cv2.selectROI("Tracking", frame, False)

# Initialize the tracker with the selected ROI
tracker.init(frame, bbox)

# Variables for calculating FPS
fps_start_time = time.time()
fps_counter = 0
fps = 0

# Function to draw bounding box and status on the image
def drawBox(img, bbox):
x, y, w, h = int(bbox[0]), int(bbox[1]), int(bbox[2]), int(bbox[3])
cv2.rectangle(img, (x, y), ((x + w), (y + h)), (0, 255, 255), 3, 3)
cv2.putText(img, "Tracking", (x, y - 10), cv2.FONT_HERSHEY_SCRIPT_SIMPLEX, 0.9, (0, 255, 255), 2, cv2.LINE_AA)

# Main loop for video processing
while True:
# Read a frame from the video
success, img = cap.read()
try:
# Read the first frame from the video
success, frame = cap.read()
if not success:
print("Failed to read video")
break

# Update the tracker with the current frame
success, bbox = tracker.update(img)

# If tracking is successful, draw the bounding box
if success:
drawBox(img, bbox)
else:
# If tracking is lost, display "Lost" message
cv2.putText(img, "Lost", (20, 40), cv2.FONT_HERSHEY_SCRIPT_SIMPLEX, 0.9, (0, 0, 255), 2, cv2.LINE_AA)

# Display status and FPS on the image
cv2.rectangle(img, (15, 15), (200, 90), (255, 0, 0), 2)
cv2.putText(img, "Status:", (20, 75), cv2.FONT_HERSHEY_SIMPLEX, 0.7, (255, 0, 0), 2)
cv2.putText(img, "Tracking", (102, 75), cv2.FONT_HERSHEY_SIMPLEX, 0.7, (0, 0, 255), 2)

# Calculate and display FPS
fps_counter += 1
fps_end_time = time.time() - fps_start_time
if fps_end_time > 1:
fps = fps_counter / fps_end_time
fps_counter = 0
fps_start_time = time.time()

cv2.putText(img, "FPS: {:.2f}".format(fps), (20, 40), cv2.FONT_HERSHEY_SIMPLEX, 0.7, (255, 255, 0), 2)

# Display the image with tracking results
cv2.imshow("Tracking", img)

# Exit the loop if 'q' is pressed
if cv2.waitKey(1) & 0xFF == ord('q'):
break

# Release the video capture and close windows
cap.release()
cv2.destroyAllWindows()
exit()

# Select the region of interest (ROI) for tracking
bbox = cv2.selectROI("Tracking", frame, False)

# Initialize the tracker with the selected ROI
tracker.init(frame, bbox)

# Variables for calculating FPS
fps_start_time = time.time()
fps_counter = 0
fps = 0

# Function to draw bounding box and status on the image
def drawBox(img, bbox):
x, y, w, h = int(bbox[0]), int(bbox[1]), int(bbox[2]), int(bbox[3])
cv2.rectangle(img, (x, y), ((x + w), (y + h)), (0, 255, 255), 3, 3)
cv2.putText(img, "Tracking", (x, y - 10), cv2.FONT_HERSHEY_SCRIPT_SIMPLEX, 0.9, (0, 255, 255), 2, cv2.LINE_AA)

# Main loop for video processing
while True:
# Read a frame from the video
success, img = cap.read()
if not success:
print("Failed to read video")
break

# Update the tracker with the current frame
success, bbox = tracker.update(img)

# If tracking is successful, draw the bounding box
if success:
drawBox(img, bbox)
else:
# If tracking is lost, display "Lost" message
cv2.putText(img, "Lost", (20, 40), cv2.FONT_HERSHEY_SCRIPT_SIMPLEX, 0.9, (0, 0, 255), 2, cv2.LINE_AA)

# Display status and FPS on the image
cv2.rectangle(img, (15, 15), (200, 90), (255, 0, 0), 2)
cv2.putText(img, "Status:", (20, 75), cv2.FONT_HERSHEY_SIMPLEX, 0.7, (255, 0, 0), 2)
cv2.putText(img, "Tracking", (102, 75), cv2.FONT_HERSHEY_SIMPLEX, 0.7, (0, 0, 255), 2)

# Calculate and display FPS
fps_counter += 1
fps_end_time = time.time() - fps_start_time
if fps_end_time > 1:
fps = fps_counter / fps_end_time
fps_counter = 0
fps_start_time = time.time()

cv2.putText(img, "FPS: {:.2f}".format(fps), (20, 40), cv2.FONT_HERSHEY_SIMPLEX, 0.7, (255, 255, 0), 2)

# Display the image with tracking results
cv2.imshow("Tracking", img)

# Exit the loop if 'q' is pressed
if cv2.waitKey(1) & 0xFF == ord('q'):
break
finally:
# Release the video capture and close windows
cap.release()
cv2.destroyAllWindows()
52 changes: 30 additions & 22 deletions Video_Capture.py
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -84,8 +84,8 @@ def stack_images(scale, img_array):
if rows_available:
# Stack images horizontally
hor = [np.hstack(img_row) for img_row in img_array]
# Stack rows vertically```python
ver = np.vstack(hor)
# Stack rows vertically
ver = np.vstack(hor)
else:
# Stack images horizontally
hor = np.hstack(img_array)
Expand All @@ -94,23 +94,31 @@ def stack_images(scale, img_array):
return cv2.resize(ver, None, fx=scale, fy=scale)


while True:
success, img = cap.read()
img = cv2.resize(img, (width_img, height_img))
img_contour = img.copy()

img_thres = preprocess_image(img)
biggest = get_contours(img_thres)

if biggest.size != 0:
img_warped = get_warp(img, biggest)
image_array = ([img_contour, img_warped])
cv2.imshow("Image Warped", img_warped)
else:
image_array = ([img_contour, img])

stacked_images = stack_images(0.6, image_array)
cv2.imshow("Capture Recording", stacked_images)

if cv2.waitKey(1) & 0xFF == ord('q'):
break
try:
while True:
success, img = cap.read()
if not success:
print("Failed to capture image")
break

img = cv2.resize(img, (width_img, height_img))
img_contour = img.copy()

img_thres = preprocess_image(img)
biggest = get_contours(img_thres)

if biggest.size != 0:
img_warped = get_warp(img, biggest)
image_array = ([img_contour, img_warped])
cv2.imshow("Image Warped", img_warped)
else:
image_array = ([img_contour, img])

stacked_images = stack_images(0.6, image_array)
cv2.imshow("Capture Recording", stacked_images)

if cv2.waitKey(1) & 0xFF == ord('q'):
break
finally:
cap.release()
cv2.destroyAllWindows()
25 changes: 13 additions & 12 deletions adjust_camera.py
View file
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Original file line number Diff line number Diff line change
Expand Up @@ -2,19 +2,20 @@

cap = cv2.VideoCapture(0) # Adjust the camera index if needed

while True:
success, frame = cap.read()
try:
while True:
success, frame = cap.read()

if not success:
print("Failed to read frame")
break
if not success:
print("Failed to read frame")
break

print(frame.shape) # Print the shape of the frame (height, width, channels)
print(frame.shape) # Print the shape of the frame (height, width, channels)

cv2.imshow("Frame", frame)
cv2.imshow("Frame", frame)

if cv2.waitKey(1) & 0xFF == ord('q'):
break

cap.release()
cv2.destroyAllWindows()
if cv2.waitKey(1) & 0xFF == ord('q'):
break
finally:
cap.release()
cv2.destroyAllWindows()
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