Coding Activities by Sreevatsav V

Famous Face Recognition 1

Let’s do this activity to recognize famous unknown faces.

Capstone 1

You have to create three tables- Salesman, Customer, and Orders and have to perform these queries: 1. Write a query to find customers with their names, salesmen with their names, and city that lives in the same city. 2. Find the names of all customers along with the salesmen who work for them 3. Display all those orders by the customers not located in the same cities where their salesmen live. 4. Find out each order number followed by the name of the customers who made the order. 5. Sort out the customer and their grade who made an order. Each customer must have a grade and serve by at least a salesman who belongs to a city. 6. Write a query which produces customers with their: name, city, commission, and salesman, who served by a salesman and salesman works at a rate of the commission within 12% to 14%, respectively. 7. Write the query which Produces all orders with the order number, customer name, commission rate & earned commission amount for the customers who carry their grade is 200 or more and are served by an existing salesman. 8. Display all customers with orders on October 5, 2012.

Customer Cupcake Shop Bot

Let’s build a simple customer cupcake shopbot that we can add to our website. Use all the steps in the Dialogflow mentioned above.

Funny Minions 1

Let’s make some funny mirror images of minions. 1. Read the image. 2. Create the virtual camera object. 3. Generate a mirror for each 3D point, and Z coordinate as Z = 20*exp^((x/w)^2 / 2*0.1*sqrt(2*pi)) 4. Display the funny mirror image.

Face Detection using OpenCV

Let’s detect some faces in an image using the HAAR Cascade. 1. Read the image. 2. Convert the Original image to a B&W image. 3. Print the coordinates where the face is located. 4. Draw a rectangle on the detected face.

Color Detection using OpenCV

Let’s detect some colors of an image using the OpenCV library. 1. Read the image. 2. Convert BGR image to HSV image. 3. Specify the color range. 4. Create the mask in the range. 5. Write the text on an image.

Shape Detection using OpenCV

Let’s detect some shapes in an image using the OpenCV library. 1. Read the image. 2. Convert the Original image to a B&W image. 3. Convert it into a threshold. 4. Find out the contours in an image.

Drawing with OpenCV 1

Let’s draw some shapes on an image using the OpenCV library. 1. Initialize the image using the NumPy array. 2. Draw the unfilled and filled square. 3. Draw the unfilled and filled circle. 4. Draw the line. 5. Write the text on an image.

Playing with Images 1

Let’s do the image processing using the OpenCV library. Change the colorful image to grayscale and HSV image. Edge Detection- Do the Erosion and Dilation of the image. Image Manipulation- Denoise the image.

Digit Recognition using CNN - Part 2

Create a Digit Recognizer model to predict the digit present in an image using Keras. First, in Part-2, perform model training on the model created in part 1 and then evaluate its performance. Next up, create functions to predict digits using the model.

Digit Recognition using CNN - Part 1

Create a Digit Recognizer model to predict the digit present in an image using Keras. In Part-1, perform data preprocessing and prepare data for feeding into the neural network. Also, create a baseline model for the same.

Image Classification using CNN - Part 1

Create an Image Classifier model to predict the object present in an image using Keras. In Part-1, perform data preprocessing and prepare data for feeding into the neural network. Also, create a baseline model for the same.