DAY-13_SUMMER_TRAINING_AI/ML(VIDEO CAPTURING) 😎

Day-13_SUMMER_TRAINING_AIML/Day-13(1)_DHRUVDHAYAL_AIML.py

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+# Background Subtraction in a Video
+
+import cv2
+
+path = r'C:\Users\pc\Downloads\Day-13\vid_mpeg4.mp4'
+vid = cv2.VideoCapture(path)
+
+if not vid.isOpened():
+    print("Error: Couldn't open video file.")
+    exit()
+
+back_subtractor = cv2.createBackgroundSubtractorMOG2(varThreshold=70, detectShadows=False)
+back_subtractor2 = cv2.createBackgroundSubtractorKNN(dist2Threshold=5000, detectShadows=False)
+
+while True:
+    ret, frame = vid.read()
+
+    if not ret:
+        break  # No more frames to read, exit the loop
+
+    mask_image = back_subtractor.apply(frame)
+    mask2_image = back_subtractor2.apply(frame)
+
+    cv2.imshow('mask', mask_image)
+    cv2.imshow('mask2', mask2_image)
+    cv2.imshow('org', frame)
+
+    if cv2.waitKey(1) & 0xFF == ord('q'):
+        break
+
+vid.release()
+cv2.destroyAllWindows()

Day-13_SUMMER_TRAINING_AIML/Day-13_DHRUVDHAYAL_AIML.py

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+# -*- coding: utf-8 -*-
+"""
+Created on Wed Jul 24 10:24:44 2024
+
+@author: student
+"""
+import cv2;
+import numpy as np;
+
+#Copy the Path of the Vedio.
+path = r"C:\Users\pc\Downloads\Day-13\vid_mpeg4.mp4";
+
+#Create the Vedio Reader Object.
+vid=cv2.VideoCapture(path);
+
+print(vid);
+print(vid.isOpened());
+
+while(vid.isOpened()):
+    val,frame=vid.read();
+    #If the frame is found to be captured.
+    if(val):
+
+        gray_im=cv2.cvtColor(frame,cv2.COLOR_BGR2GRAY);
+        ycrcb_im=cv2.cvtColor(frame,cv2.COLOR_BGR2YCrCb);
+        hsv_im=cv2.cvtColor(frame,cv2.COLOR_BGR2HSV);
+
+    cv2.imshow('Frame',gray_im);
+    cv2.imshow('HSV',hsv_im);
+    cv2.imshow('YCrCb',ycrcb_im);
+    cv2.imshow('Original',frame);
+    if(cv2.waitKey(1)==ord('q')):
+        break;
+
+#Close the Values of the Objects.
+vid.release();
+cv2.destroyAllWindows();
+print(frame_counter());

Day-13_SUMMER_TRAINING_AIML/ImageRecognizations.py

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+# using opencv read the video file anf run it frame 
+#by frame 
+# in python environment
+import cv2
+import numpy as np
+# copy the path of the video
+#path = 'C:\\Users\\pc\\vid_mpeg4.mp4'
+path = r"C:\Users\pc\Downloads\Day-13\VIRAT_S_050201_05_000890_000944.mp4";
+# mouse click event 
+def mouseRGB (event, x,y,flag,param):
+    if(event==cv2.EVENT_FLAG_LBUTTON):
+        colorB = frame[x,y,0]
+        colorG = frame[x,y,1]
+        colorR = frame[x,y,2]
+        print('BGR values:',colorB,colorG,colorR)
+        print('corr:',x,y)
+
+cv2.namedWindow('Frame')
+cv2.setMouseCallback('Frame', mouseRGB)
+# create the video reader object
+vid = cv2.VideoCapture(path)
+print(vid)
+print(vid.isOpened())
+frame_counter=0
+val,frame=vid.read()
+image_hsv=cv2.cvtColor(frame, cv2.COLOR_BGR2HSV)
+cv2.imshow('Frame',image_hsv)
+
+# ROI - region of interest Bmin - 71 , Bmax = 142
+# Gmin - 94 , Gmax 218
+# R min=120 R max = 235
+while(1):        
+    if(cv2.waitKey(1)==ord('q')):
+        break
+
+vid.release() # close the object
+cv2.destroyAllWindows()
+
+print(frame_counter)    

Day-13_SUMMER_TRAINING_AIML/Test.py

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+# -*- coding: utf-8 -*-
+"""
+Created on Wed Jul 24 10:24:44 2024
+
+@author: student
+"""
+
+#=========================================== Using the KNN! ===============================================
+
+import cv2;
+import numpy as np;
+import imutils;
+
+#Copy the Path of the Vedio.
+path = r"C:\Users\pc\Downloads\Day-13\VIRAT_S_050201_05_000890_000944.mp4";
+
+#Backgroud Substractor.
+#bsck_gd = cv2.getStructuringElement(cv2.MORPH_ELLIPSE,(3,3));
+back_substractor = cv2.createBackgroundSubtractorKNN(dist2Threshold=8000);
+
+#Create the Vedio Reader Object.
+vid=cv2.VideoCapture(path);
+print(vid);
+print(vid.isOpened());
+frame_counter=0;
+#while(vid.isOpened()):
+f=0;
+while(f<=1000):
+    f=f+1;
+    val,frame=vid.read();
+    #Vedio Background Substractions.
+    mask_image = back_substractor.apply(frame);
+    cnts=cv2.findContours(mask_image,cv2.RETR_TREE,cv2.CHAIN_APPROX_SIMPLE);
+    final_contours=imutils.grab_contours(cnts);
+
+    for c in final_contours:
+        area=cv2.contourArea(c);
+        if(area>250):
+            print(area);
+            M=cv2.moments(c);
+            cx=int(M['m10']/M['m00']);
+            cy=int(M['m01']/M['m00']);
+            cv2.drawContours(frame,[c],-1,(0,0,255));
+            cv2.circle(frame,(cx,cy),4,(0,255,0));
+
+    cv2.imshow('mask',mask_image);
+    cv2.imshow('original',frame);
+    if(cv2.waitKey(1)==ord('q')):
+        break;
+
+#Close the Values of the Objects.
+vid.release();
+cv2.destroyAllWindows();
+print(frame_counter());

Day-13_SUMMER_TRAINING_AIML/VedioColorBased(Camera).py

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+import cv2
+import numpy as np
+import imutils
+
+# Define HSV thresholds for the color of interest
+lowHSV = np.array([75, 100, 119])
+highHSV = np.array([142, 218, 235])
+
+# IP Webcam server address (replace with your device's IP and port)
+ip_address = '192.168.137.188';  # Example: '192.168.0.100'
+port = '4747';  # Example: '8080'
+url = f'http://{ip_address}:{port}/video';  # Correctly formatted URL string
+
+# Initialize video capture from IP Webcam stream
+vid = cv2.VideoCapture(url)
+
+frame_counter = 0
+xCORR = []
+yCORR = []
+
+while vid.isOpened():
+    ret, frame = vid.read()
+    frame_counter += 1
+
+    if ret:
+        # Convert frame to HSV
+        hsv = cv2.cvtColor(frame, cv2.COLOR_BGR2HSV)
+
+        # Create a mask using HSV thresholds
+        mask = cv2.inRange(hsv, lowHSV, highHSV)
+
+        # Find contours in the mask
+        contours = cv2.findContours(mask, cv2.RETR_TREE, cv2.CHAIN_APPROX_SIMPLE)
+        contours = imutils.grab_contours(contours)
+
+        # Process each contour
+        for c in contours:
+            area = cv2.contourArea(c)
+            if area > 200:
+                M = cv2.moments(c)
+                if M['m00'] != 0:
+                    cx = int(M['m10'] / M['m00'])
+                    cy = int(M['m01'] / M['m00'])
+                    cv2.drawContours(frame, [c], -1, (0, 0, 255), 2)
+                    cv2.circle(frame, (cx, cy), 4, (0, 255, 0), -1)
+                    xCORR.append(cx)
+                    yCORR.append(cy)
+                    frame[cy, cx] = (0, 0, 255)
+
+        cv2.imshow('Frame', frame)
+
+        if cv2.waitKey(1) & 0xFF == ord('q'):
+            break
+
+vid.release()
+cv2.destroyAllWindows()

Day-13_SUMMER_TRAINING_AIML/VedioColorBased.py

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+# color based ROI detection
+# ROI - region of interest Bmin - 71 , Bmax = 142
+# Gmin - 94 , Gmax 218
+# R min=120 R max = 235
+
+import cv2
+import numpy as np
+import imutils
+h=75;s=100;v=119
+lowBGR = np.array([0,98,115])
+highBGR =np.array([99,157,255]) 
+# copy the path of the video
+#path = 'C:\\Users\\pc\\vid_mpeg4.mp4'
+path = r"C:\Users\pc\Downloads\Day-13\VIRAT_S_050201_05_000890_000944.mp4";
+
+# create the video reader object
+vid = cv2.VideoCapture(path)
+print(vid)
+print(vid.isOpened())
+frame_counter=0
+xCORR= []
+yCORR= []
+c_list = []
+while(vid.isOpened()):
+    val,frame=vid.read()
+    image_hsv=cv2.cvtColor(frame, cv2.COLOR_BGR2HSV)
+    frame_counter +=1
+    # if the frame is captured
+    if(val):
+        mask_image = cv2.inRange(image_hsv,
+                                (lowBGR),
+                                (highBGR))
+        # find contours
+        cnts = cv2.findContours(mask_image, cv2.RETR_TREE, cv2.CHAIN_APPROX_SIMPLE)
+        final_contours = imutils.grab_contours(cnts)
+        if(frame_counter==1):
+            frame_original=frame.copy()
+
+        count=0
+        #big object detection
+        for c in final_contours:
+
+            area = cv2.contourArea(c)
+            if(area>200):
+                print(area)
+                count=count+1
+                print(count)
+
+                M = cv2.moments(c)
+                cx = int(M['m10']/M['m00'])
+                cy = int(M['m01']/M['m00'])
+                # c have every info about contour
+                cv2.drawContours(frame, [c], -1, (0,0,255))
+                cv2.circle(frame, (cx,cy), 4 ,(0,255,0))
+                xCORR.append(cx)
+                yCORR.append(cy)
+                line_thickness = 2
+
+                for i in range(len(xCORR)):
+                    frame[yCORR[i],xCORR[i]]= (0,0,255)
+
+
+                cv2.imshow('Frame',frame)
+                #cv2.imshow('mask_image',mask_image)
+
+    if(cv2.waitKey(1)==ord('q')):
+        break
+
+
+
+vid.release() # close the object
+cv2.destroyAllWindows()
+
+print(frame_counter)