This is my contribution page.[NAME :- ANKIT KUMAR GUPTA]
->learned to use marker-based image segmentation using watershed algorithm.
->went through the code and thery concepts of Blending Images of Different Sizes,and Blending and Pasting Images commonly known as Arithmetic Image Operations,as we only deal with the pixels and its operation.
-> read about contours , its uses and funtions,with examples like :- hsv = cv2.cvtColor(image , cv2.COLOR_BGR2HSV)
-> read the Finding extreme points in contours with OpenCV docs. Saw an example of hand gesture recognition.
-> saw various contexts and read about them. 1. Blending 2. Blurring and smoothing 3. Color mapping 4.Corner detection 5.Edge detection 6.Grid detection
->Circle based grid and its applications.
-> went through the FLASK framework and learnt its working with the algorithm SVM(Support Vector Machine),which is built in python.
1. templates - folder containing the HTML files.
2. static- folder containing files, like images.
3. aap.py - a python file where we have built our application.
4. iri.pkl - a file with ,saved model.
5. iris.py - a python file where the model is built.
-> learnt about Face and Eye detection that works on the algorithm called "Haar Classifier".
-> went through the prerequisites for it ans the system requirements with installing and a bit of code.
-> Haar Classifier is a machine learning based approach where a function is trained from a lot of inputs based on true and false directed images / any model related data.
This is my contribution page.[NAME :- ANKIT KUMAR GUPTA]
->learned to use marker-based image segmentation using watershed algorithm.
->went through the code and thery concepts of Blending Images of Different Sizes,and Blending and Pasting Images commonly known as Arithmetic Image Operations,as we only deal with the pixels and its operation.
->explored the:- 1.resize(), 2.bitwise_not(), 3.addWeighted() and, 4.cvtColor() functions.
-> read about contours , its uses and funtions,with examples like :- hsv = cv2.cvtColor(image , cv2.COLOR_BGR2HSV)
-> read the Finding extreme points in contours with OpenCV docs. Saw an example of hand gesture recognition.
-> saw various contexts and read about them. 1. Blending 2. Blurring and smoothing 3. Color mapping 4.Corner detection 5.Edge detection 6.Grid detection ->Circle based grid and its applications.
-> went through the FLASK framework and learnt its working with the algorithm SVM(Support Vector Machine),which is built in python.
-> learnt about Face and Eye detection that works on the algorithm called "Haar Classifier".
-> went through the prerequisites for it ans the system requirements with installing and a bit of code.
-> Haar Classifier is a machine learning based approach where a function is trained from a lot of inputs based on true and false directed images / any model related data.