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Why does the cropped video not get saved?

Here, I have a code that takes a video as input and let the user draw a ROI. Later the cropped video will be displayed. This code was originally taken from I would like to define a Region of Interest in a video and only process that area.
I have provided the code below.
Question: I would like to save the cropped video in .mp4 format. The video output shows only a 1kb file. Can you go through the code and suggest a solution?
NB: I went through answer provided at OpenCV video not getting saved. Still I have failed to figure out the error.
import numpy as np
import cv2
import matplotlib.pyplot as plt
ORIGINAL_WINDOW_TITLE = 'Original'
FIRST_FRAME_WINDOW_TITLE = 'First Frame'
DIFFERENCE_WINDOW_TITLE = 'Difference'
canvas = None
drawing = False # true if mouse is pressed
#Retrieve first frame
def initialize_camera(cap):
_, frame = cap.read()
return frame
# mouse callback function
def mouse_draw_rect(event,x,y,flags, params):
global drawing, canvas
if drawing:
canvas = params[0].copy()
if event == cv2.EVENT_LBUTTONDOWN:
drawing = True
params.append((x,y)) #Save first point
elif event == cv2.EVENT_MOUSEMOVE:
if drawing:
cv2.rectangle(canvas, params[1],(x,y),(0,255,0),2)
elif event == cv2.EVENT_LBUTTONUP:
drawing = False
params.append((x,y)) #Save second point
cv2.rectangle(canvas,params[1],params[2],(0,255,0),2)
def select_roi(frame):
global canvas
#here, it is the copy of the first frame.
canvas = frame.copy()
params = [frame]
ROI_SELECTION_WINDOW = 'Select ROI'
cv2.namedWindow(ROI_SELECTION_WINDOW)
cv2.setMouseCallback(ROI_SELECTION_WINDOW, mouse_draw_rect, params)
roi_selected = False
while True:
cv2.imshow(ROI_SELECTION_WINDOW, canvas)
key = cv2.waitKey(10)
#Press Enter to break the loop
if key == 13:
break;
cv2.destroyWindow(ROI_SELECTION_WINDOW)
roi_selected = (3 == len(params))
print(len(params))
if roi_selected:
p1 = params[1]
p2 = params[2]
if (p1[0] == p2[0]) and (p1[1] == p2[1]):
roi_selected = False
#Use whole frame if ROI has not been selected
if not roi_selected:
print('ROI Not Selected. Using Full Frame')
p1 = (0,0)
p2 = (frame.shape[1] - 1, frame.shape[0] -1)
return roi_selected, p1, p2
if __name__ == '__main__':
cap = cv2.VideoCapture(r'E:\cardiovascular\brad1low.mp4')
#Grab first frame
first_frame = initialize_camera(cap)
#Select ROI for processing. Hit Enter after drawing the rectangle to finalize selection
roi_selected, point1, point2 = select_roi(first_frame)
#Grab ROI of first frame
first_frame_roi = first_frame[point1[1]:point2[1], point1[0]:point2[0]]
print(f'first frame roi is {first_frame_roi}')
#An empty image of full size just for visualization of difference
difference_image_canvas = np.zeros_like(first_frame)
out = cv2.VideoWriter(r'E:\cardiovascular\filename2.mp4', cv2.VideoWriter_fourcc(*'MP4V'), int(cap.get(cv2.CAP_PROP_FRAME_COUNT)), (int(first_frame_roi.shape[0]), (int(first_frame_roi.shape[1]))))
while cap.isOpened():
ret, frame = cap.read()
if ret:
#ROI of current frame
roi = frame[point1[1]:point2[1], point1[0]:point2[0]]
print(f'roi is {roi}')
cv2.imshow(DIFFERENCE_WINDOW_TITLE, roi)
out.write(roi)
key = cv2.waitKey(30) & 0xff
if key == 27:
break
else:
break
cap.release()
out.release()
cv2.destroyAllWindows()

Apply mask to Webcam streaming in opencv

I applied mask to video feed using OpenCV and want to display the Live streaming on the website but the following code stops streaming once it starts. I've been wrapping my head around but couldn't figure out the solution. Any help would be greatly appreciated.
views.py
def gen(frame):
while True:
# frame = camera.get_frame()
yield (b'--frame\r\n'
b'Content-Type: image/jpeg\r\n\r\n' + frame + b'\r\n\r\n')
#api_view(['GET'])
def seasoncolor(request):
while True:
return StreamingHttpResponse(gen(color_detection.color_detection(0)),
content_type='multipart/x-mixed-replace; boundary=frame')
color_detection.py
import numpy as np
import cv2
import sys
'''
ML object detection algo(haarcascade)used to identify objects.
the XML file consists of trained Haar Cascade models.
'''
def color_detection(season):
face_cascade = cv2.CascadeClassifier(
'accounts/personal_color/self_detection/haarcascade_frontalface_default.xml')
# 'accounts/personal_color/self_detection/haarcascade_frontalface_default.xml'
# initialize video from the webcam
video = cv2.VideoCapture(1)
# Spring/summer/fall/winter
while True:
# ret tells if the camera works properly. Frame is an actual frame from the video feed
ret, frame = video.read()
# make sure port is working and read the image
if frame is not None and video.isOpened():
gray = cv2.cvtColor(frame, cv2.COLOR_BGR2GRAY)
'''
Detect the faces within the subregions of the image in scales
scaleFactor indicates how much the image size is reduced at each image scale.
minNeighbors: Higher value results in higher quality of the detected face.
'''
faces = face_cascade.detectMultiScale(
gray, scaleFactor=1.1, minNeighbors=6)
# Draw the rectangle around each face
for (x, y, w, h) in faces:
# Use the stcoordinates to find the center of the face and from that point draw a rectangle of radius w/2 or h/2.
center_coordinates = x + w // 2, y + h // 2
radius = w // 2 # or can be h / 2 or can be anything based on your requirements
# background color(black)
mask = np.zeros(frame.shape[:2], dtype="uint8")
# Draw the desired region to crop out in white
cv2.circle(mask, center_coordinates, radius, (255, 255, 255), -1)
masked = cv2.bitwise_and(frame, frame, mask=mask)
if int(season) ==0: # Spring
# Replace all (0,0,0)channel with Coral pink
masked[np.where((masked == [0, 0, 0]).all(axis=2))] = [121, 131, 248]
elif int(season) ==1: # Summer
#Replace all (0,0,0)channel with Rose Red
masked[np.where((masked==[0,0,0]).all(axis=2))]=[86,30,194]
elif int(season) ==2: # Fall
#Replace all (0,0,0)channel with Red Brown /Cinnamon
masked[np.where((masked==[0,0,0]).all(axis=2))]=[30,105,210]
else: # Winter
#Replace all (0,0,0)channel with Burgundy Red
masked[np.where((masked==[0,0,0]).all(axis=2))]=[31,2,141]
# cv2.imshow('mask applied', masked)
ret, jpeg = cv2.imencode('.jpg', masked)
return jpeg.tobytes()
if cv2.waitKey(30) & 0xff == 27:
break
video.release()
cv2.destroyAllWindows()
if __name__ == '__main__':
arg = sys.argv[1]
color_detection(arg)
Self_color_diagnosis.js
import React, { useState, useEffect } from 'react';
import ReactDOM from 'react-dom';
import CameraScreen from './CameraScreen';
import { StyleSheet, Text, View, Image } from 'react-native';
import { NavigationContainer } from '#react-navigation/native';
import { createStackNavigator } from '#react-navigation/stack';
import axios from 'axios';
function Self_color_diagnosis({navigation,route}) {
return (
<View style={styles.title_container}>
<Image style={styles.video} source={{
uri: 'http://localhost:8000/seasoncolor/',}}/>
</View>
);
}
const styles = StyleSheet.create({
video: {
width: 500,
height: 500
},
title_container: {
flex: 1,
justifyContent: 'center'
},
});
export default Self_color_diagnosis;
The above code results in the pic below. The streaming stops and does not change at all.

gen() runs loop which all time uses the same frame().
You have to get frame inside this loop.
def gen():
while True:
frame = color_detection.color_detection(0)
if frame:
yield b'--frame\r\nContent-Type: image/jpeg\r\n\r\n' + frame + b'\r\n\r\n'
#else:
# print('no frame')
But color_detection should run without loop.
And you should create VideoCapture(1) only once.
And you should return frame even if you didn't detect any face.
path = os.path.join(cv2.data.haarcascades, 'haarcascade_frontalface_default.xml')
face_cascade = cv2.CascadeClassifier(path)
video = cv2.VideoCapture(1)
def color_detection(season):
# ret tells if the camera works properly. Frame is an actual frame from the video feed
ret, frame = video.read()
# make sure port is working and read the image
if frame is not None and video.isOpened():
gray = cv2.cvtColor(frame, cv2.COLOR_BGR2GRAY)
'''
Detect the faces within the subregions of the image in scales
scaleFactor indicates how much the image size is reduced at each image scale.
minNeighbors: Higher value results in higher quality of the detected face.
'''
faces = face_cascade.detectMultiScale(gray, scaleFactor=1.1, minNeighbors=6)
# Draw circle around each face
for (x, y, w, h) in faces:
# Use the stcoordinates to find the center of the face and from that point draw a rectangle of radius w/2 or h/2.
center_coordinates = x + w // 2, y + h // 2
radius = w // 2 # or can be h / 2 or can be anything based on your requirements
# background color(black)
mask = np.zeros(frame.shape[:2], dtype="uint8")
# Draw the desired region to crop out in white
cv2.circle(mask, center_coordinates, radius, (255, 255, 255), -1)
masked = cv2.bitwise_and(frame, frame, mask=mask)
if season == 0: # Spring
# Replace all (0,0,0)channel with Coral pink
masked[np.where((masked == [0, 0, 0]).all(axis=2))] = [121, 131, 248]
elif season == 1: # Summer
#Replace all (0,0,0)channel with Rose Red
masked[np.where((masked==[0,0,0]).all(axis=2))] = [86,30,194]
elif season == 2: # Fall
#Replace all (0,0,0)channel with Red Brown /Cinnamon
masked[np.where((masked==[0,0,0]).all(axis=2))] = [30,105,210]
else: # Winter
#Replace all (0,0,0)channel with Burgundy Red
masked[np.where((masked==[0,0,0]).all(axis=2))] = [31,2,141]
ret, jpeg = cv2.imencode('.jpg', masked)
else: # it is `for/else` construction, not `if/else`
ret, jpeg = cv2.imencode('.jpg', frame)
return jpeg.tobytes()
#return None
BTW:
I see other problem. When it detects many faces then it creates new mask for every face and assigns every mask to original image - so every mask skip previous mask - so it should show only last face, and hide other faces. You should first create one mask with all circles and next use it on image.
EDIT:
I don't know what web framework you use so I used Flask to create minimal working example.
import os
from flask import Flask, Response
import cv2
import numpy as np
app = Flask(__name__)
print('\n'.join(sorted(os.listdir(cv2.data.haarcascades))))
path = os.path.join(cv2.data.haarcascades, 'haarcascade_frontalface_default.xml')
face_cascade = cv2.CascadeClassifier(path)
#video = cv2.VideoCapture(0) # my webcam
video = cv2.VideoCapture(0) # your webcam
def color_detection(season):
ret, frame = video.read()
if frame is not None and video.isOpened():
gray = cv2.cvtColor(frame, cv2.COLOR_BGR2GRAY)
faces = face_cascade.detectMultiScale(gray, scaleFactor=1.1, minNeighbors=6)
# test two circles on image 640x480
#faces = [[100, 100, 250, 250], [640-100-250, 480-100-250, 250, 250]]
if len(faces) > 0: # it can be `if faces:` because `faces` is `numpy array` which need different method to check if not empty
# background color(black)
mask = np.zeros(frame.shape[:2], dtype="uint8")
# draw all circles on mask
for (x, y, w, h) in faces:
#print(x, y, w, h)
# use the coordinates to find the center of the face and from that point draw a rectangle of radius w/2 or h/2.
center_coordinates = x + w // 2, y + h // 2
radius = max(w, h) // 2 # or can be h / 2 or can be anything based on your requirements
# draw the desired region to crop out in white
cv2.circle(mask, center_coordinates, radius, (255, 255, 255), -1)
# use mask with all circles
masked = cv2.bitwise_and(frame, frame, mask=mask)
if season == 0: # Spring - Coral pink
color = [121, 131, 248]
elif season == 1: # Summer - Rose Red
color = [86,30,194]
elif season == 2: # Fall - Red Brown /Cinnamon
color = [30,105,210]
else: # Winter - Burgundy Red
color = [31,2,141]
masked[np.where((masked == [0,0,0]).all(axis=2))] = color
else: # no faces
masked = frame
ret, jpeg = cv2.imencode('.jpg', masked)
return jpeg.tobytes()
def gen():
while True:
frame = color_detection(0)
if frame:
yield (b'--frame\r\nContent-Type: image/jpeg\r\n\r\n' + frame + b'\r\n\r\n')
#else:
# print('no frame')
#app.route('/')
def index():
return '<image src="/seasoncolor">'
#app.route('/seasoncolor')
def seasoncolor():
return Response(gen(), mimetype='multipart/x-mixed-replace; boundary=frame')
if __name__ == '__main__':
#app.debug = True
app.run()
BTW:
To make sure: VideoCapture can work only with local camera where you run web server. It can't work with remote camera on user computer. Only user's browser has access to its camera. To work with remote camera on user computer you would have to use JavaScript to access camera in user browser and send frames to server - like in my examples in my GitHub python-examples: web camera in browser - canvas - take image and upload to server

Sending ROS messages through a cv2 python script

I am trying to implement a robotic solution, where the user will click on a point through a camera feed of an area and the mobile 4 wheel robot will path its way to that location.
I have created the part of translating video pixel coordinates to ground coordinates through the use of the homograph transformation and would like to implement the part of sending the ground coordinates to RViz.
The part of calculating the ground coordinates is shown bellow:
global h
font = cv2.FONT_HERSHEY_SIMPLEX #Loading neccessary fonts
with open("save.h", "rb") as f:
h = load(f)
print "Homographic matrix loaded successfully."
def draw_circle2(event,x,y,flags,param):
global h,mouseX,mouseY, num_of_points, complete,np_coord_on_screen,np_coord_on_ground, myImage, emptyFrame, coord_on_screen, coord_on_ground
if event == cv2.EVENT_LBUTTONDBLCLK:
a = np.array([[x, y]], dtype='float32')
a = np.array([a])
pointOut = cv2.perspectiveTransform(a, h) #Calculation of new point location
loc_pointOut = tuple(pointOut)
pointOut=(loc_pointOut[0][0][0],loc_pointOut[0][0][1]) #Point on ground
print "Current Location: "+str(pointOut)
cv2.imshow('Video',emptyFrame) #Showing emptyFrame
cv2.circle(myImage,(x,y),4,(255,0,0),-1) #Draw a circle on myImage
cv2.putText(myImage,(str((round(pointOut[0],2)))+","+str(round(pointOut[1],2))), (x-5,y-15),font, 0.4,(0,255,0)) #Draw the text
cv2.imshow('Video',myImage) #Showing resulting myImage
myImage = emptyFrame.copy()
# Initial code
# Showing first frame on screen
raw_input("Press any key...")
clear_all()
cv2.namedWindow('Video') #Naming the window to use.
cv2.setMouseCallback('Video',draw_circle2) #Set mouse callBack function.
ret, frame = cap.read() #Get image from camera
if (ret): #If frame has image, show the image on screen
global myImage, emptyFrame
myImage = frame.copy()
emptyFrame = frame.copy()
cv2.imshow('Video',myImage) # Show the image on screen
while True: # making a loop
if cv2.waitKey(1) & 0xFF == ord('q'):
break
if (cv2.waitKey(1) & 0xFF == ord('c')):
#Deleting points from image
cv2.imshow('Video',emptyFrame) #Show the image again, deleting all graphical overlays like text and shapes
coord_on_screen = [] #Resetting coordinate lists
coord_on_ground=[] #Resetting coordinate lists
if (cv2.waitKey(1) & 0xFF == ord('s')):
cap.release()
cv2.destroyAllWindows()
init()
# When everything done, release the capture
cap.release()
cv2.destroyAllWindows()
So, pointOut is the point on the ground (example: (2,4) m)
I need some directions on how to implement the creation of a node and the transmission of the pointOut Marker message to a ROS topic in my code.
My configuration is ROS Kinetic Kame, Python 2.7

How to read a frame (raw_Image) from a virtual turtlebot's camera in Gazebo, and manipulate it using OpenCV and publish for viewing in Rviz

For my class robotics project, we are required to read in video feed frame by frame from a virtual turtlebot being simulated using gazebo. Then we detect colors in this image (red, blue, and green) if they are at the center of the image, within a rectangle that we have to draw in the center of the frame. If one of the colors are detected, the rectangle should change from green to red, and if the 's' button is clicked while the rectangle is red (ie it detects a color) then it should publish to a topic saying that the target was shot. The majority of this code was written for a previous assignment, in which we had to detect any of these colors anywhere in a frame from a webcam and indicate it with a bounding box or circle, and my code worked for that assignment. Now I have changed my code slightly to read frames from the virtual camera, and I added some code from some example code that our professor provided us with to try to publish the modified image so that I can view it using Rviz. Whatever I added is making the code no longer work as it should and I am getting an error, but I don't understand the code deeply enough to find my error.
The error that I am receiving is as follows:
[ERROR] [1575253473.863051, 2724.055000]: bad callback:
Traceback (most recent call last):
File "/opt/ros/melodic/lib/python2.7/dist-packages/rospy/topics.py", line 750, in _invoke_callback
cb(msg)
File "/home/project_ws/src/project_gazebo/scripts/color_detect.py", line 49, in ImageCallback
upper_left(int(w/4), h)
TypeError: 'NoneType' object is not callable
I have no idea what this means or how to fix it. I know that it is probably a problem with the subscriber callback function, but I tried to write it exactly how the professor's example did for face detection (rather than color detection). Other than that, I have no idea how to fix this issue. I could really use some guidance.
Here is what the file looks like (I would only post a snippet, but since I am unsure where the issue is I am posting all of it):
#!/usr/bin/env python
from __future__ import print_function
from collections import deque
import numpy as np
import cv2
import sys
import rospy
import rospkg
from std_msgs.msg import String
from sensor_msgs.msg import Image
from cv_bridge import CvBridge, CvBridgeError
hit_pub = rospy.Publisher('Cait/hit', String, queue_size=10)
image_pub = rospy.Publisher("Cait/image_topic_2",Image, queue_size=10)
bridge = CvBridge()
frame = None
height= None
width= None
upper_left=None
lower_right=None
inRange= False
targetHit = False
def ImageCallback(data):
try:
global frame
frame = bridge.imgmsg_to_cv2(data, "bgr8")
#frame = data.data
global height
global width
(h, w) = frame.shape[:2] #w:image-width and h:image-height
height = h
width = w
global centerPoint_x
global centerPoint_y
centerPoint_x = w/2
centerpoint_y= h/2
global upper_left
global lower_right
upper_left(int(w/4), h)
lower_right(int(w*3/4), 0)
except CvBridgeError as e:
print(e)
image_sub = rospy.Subscriber("Cait/camera/rgb/image_raw",Image,ImageCallback)
def Image_converter():
# define the lower and upper boundaries of the colors in the HSV color space
lower = {'red':(166, 84, 141), 'green':(66, 122, 129), 'yellow':(23, 59, 119)}
upper = {'red':(186,255,255), 'green':(86,255,255), 'yellow':(54,255,255)}
# grab frames from webcam -> now grab fromm rviz raw_image in subscriber
#camera = cv2.VideoCapture(0)
# keep looping
while True:
# grab the current frame -> now done by ImageCallback()
#(grabbed, frame) = camera.read()
hsv = cv2.cvtColor(frame, cv2.COLOR_BGR2HSV)
#for each color in dictionary check object in frame
#draw rectangle in the center of the frame
cv2.rectangle(frame, upper_left, lower_right, (0, 255, 0), 2)
for key, value in upper.items():
# construct a mask for the color from dictionary`1, then remove any small blobs left in the mask
kernel = np.ones((9,9),np.uint8)
mask = cv2.inRange(hsv, lower[key], upper[key])
mask = cv2.morphologyEx(mask, cv2.MORPH_OPEN, kernel)
mask = cv2.morphologyEx(mask, cv2.MORPH_CLOSE, kernel)
# find contours in the mask and initialize the current (x, y) center of the ball
cnts = cv2.findContours(mask.copy(), cv2.RETR_EXTERNAL,
cv2.CHAIN_APPROX_SIMPLE)[-2]
center = None
# only proceed if at least one contour was found
if len(cnts) > 0:
# find the largest contour in the mask, then use it to compute the minimum enclosing circle
c = max(cnts, key=cv2.contourArea)
((x, y), radius) = cv2.minEnclosingCircle(c)
#check to see if the point found is at the center of the screen, and if yes change the color of the rectangle
global inRange
if (x > int(width/4) & x< int(width*3/4)):
if(y > 0 & y < height):
cv2.rectangle(frame, upper_left, lower_right, (0, 0, 255), 2)
inRange = True
else:
cv2.rectangle(frame, upper_left, lower_right, (0, 255, 0), 2)
inRange= False
# show the frame to our screen
cv2.imshow("Image window", frame)
key = cv2.waitKey(1) & 0xFF
try:
image_pub.publish(bridge.cv2_to_imgmsg(frame, "bgr8"))
except CvBridgeError as e:
print(e)
# if the 's' key is pressed, publish an answer to the topic
if key == ord("s"):
if (inRange):
hit_pub.publish("Target hit!")
else:
hit_pub.publish("Sorry. Nothing was hit.")
if key == ord("q"): #q quits loop
break
def main(args):
rospy.init_node('image_converter', anonymous=True)
Image_converter()
try:
rospy.spin()
except KeyboardInterrupt:
print("Shutting down")
cv2.destroyAllWindows()
if __name__ == '__main__':
main(sys.argv)

Opencv python crashes after certain time

In my code after certain time (depend of the PC or OS) crashes. The error displayed is
libpng warning: Image width is zero in IHDR
libpng warning: Image height is zero in IHDR
libpng error: Invalid IHDR data
My code draw ROI on a video from webcam and take a snapshot. The ROI is deleted after 5-10 minutes (I'm not sure why, this is the error) and the picture saved not have dimensions then the error above is displayed but I'm not find the error. The instructions are, press "c" to stop the video and draw a ROI, press again "c" to take the picture, press "r" to resume the video, and repeat if you need another pictures.
I tested the code in Windows 10 and raspbian on a raspberry and the time is not the same but on both the program crashes. This is my code:
import cv2
# python PSI_Camera_test.py
class staticROI(object):
def __init__(self):
self.capture = cv2.VideoCapture(0)
self.capture.set(cv2.CAP_PROP_FRAME_WIDTH, 1280)
self.capture.set(cv2.CAP_PROP_FRAME_HEIGHT, 720)
# Bounding box reference points and boolean if we are extracting coordinates
self.image_coordinates = []
self.extract = False
self.selected_ROI = False
self.img_counter = 0
self.update()
def update(self):
while True:
if self.capture.isOpened():
# Read frame
(self.status, self.frame) = self.capture.read()
cv2.imshow('image', self.frame)
key = cv2.waitKey(2)
# Crop image
if key == ord('c'):
self.clone = self.frame.copy()
cv2.namedWindow('image')
cv2.setMouseCallback('image', self.extract_coordinates)
while True:
key = cv2.waitKey(2)
cv2.imshow('image', self.clone)
# Crop and display cropped image
if key == ord('c'):
self.crop_ROI()
img_name = "Images\opencv_frame_{}.png".format(
self.img_counter)
cv2.imwrite(img_name, self.cropped_image)
print("{} written!".format(img_name))
self.img_counter += 1
# Resume video
if key == ord('r'):
break
# Close program with keyboard 'esp'
if key % 256 == 27:
cv2.destroyAllWindows()
exit(1)
else:
pass
def extract_coordinates(self, event, x, y, flags, parameters):
# Record starting (x,y) coordinates on left mouse button click
if event == cv2.EVENT_LBUTTONDOWN:
self.image_coordinates = [(x, y)]
self.extract = True
# Record ending (x,y) coordintes on left mouse bottom release
elif event == cv2.EVENT_LBUTTONUP:
self.image_coordinates.append((x, y))
self.extract = False
self.selected_ROI = True
# Draw rectangle around ROI
cv2.rectangle(
self.clone, self.image_coordinates[0], self.image_coordinates[1], (0, 255, 0), 2)
# Clear drawing boxes on right mouse button click
elif event == cv2.EVENT_RBUTTONDOWN:
self.clone = self.frame.copy()
self.selected_ROI = False
def crop_ROI(self):
if self.selected_ROI:
self.cropped_image = self.frame.copy()
x1 = self.image_coordinates[0][0]
y1 = self.image_coordinates[0][1]
x2 = self.image_coordinates[1][0]
y2 = self.image_coordinates[1][1]
self.cropped_image = self.cropped_image[y1:y2, x1:x2]
print('Cropped image: {} {}'.format(
self.image_coordinates[0], self.image_coordinates[1]))
else:
print('Select ROI to crop before cropping')
# python PSI_Camera_test.py
if __name__ == '__main__':
static_ROI = staticROI()
Thanks in advance!