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Hacky Hour 20: Hacky Hour Trivia

By Komal Devjani Dec 28, 2020

HHH Trivia-1

Hacky Hour Trivia

This special holiday hacky hour is a chance for you to test your knowledge about alwaysAI and computer vision! If you missed it, no worries, you can test your knowledge with the Hacky Hour quiz below. The answers are located at the bottom of the blog. For explanations, watch the Hacky Hour Trivia video below.

1. Where is the origin for the Numpy axis 0,0?

A. top left corner
B. right bottom corner
C. Middle
D. Bottom left corner


2. What tool does alwaysAI’s Model Training Toolkit use to annotate model data?

A. Supervise.ly
B. CVAT
C. LabelImg
D. You can’t annotate data with alwaysAI


3. What format do you need to export your dataset in for model training using alwaysAI?

A. Pascal VOC
B. Coco
C. JSON
D. Yolo


4. What parameter in EdgeIQ ensures that your file video feed can run in real-time regardless of the inference time of the model?

A. record_realtime=True
B. realtime_play=True
C. drop_frames=True
D. play_realtime=True


5. Which of the following is NOT an example of a finite state machine?

A. Elevator
B. Traffic Light
C. Stop Sign
D. Thermostat


6. Which tool would you use to deploy/update a CV application onto multiple edge devices in the field?

A. Balena Etcher
B. CVAT
C. Supervise.ly
D. Eyecloud


7. Which annotation setting tracks bounding boxes in multiple frames (CVAT)?

A. Interpolation/Track
B. Shape/Annotate
C. Extrapolation/Track
Box/Follow


8. How do you activate the Python virtual environment, which will have all the required packages installed?

A. aai Python virtual environment
B. source venv/bin/activate
C. aai app configure
D. Python3


9. Which of the following is not an application of computer vision?

A. Home Automation
B. Waste Management
C. NLP
D. Retail Analytics


10. Which command do you use to train a model in Jupyter?

A. aai train --Jupyter
B. aai dataset train --Jupyter
C. aai dataset train
D. aai model train --Jupyter


11. What types of models can you train using alwaysAI?

A. Image classification
B. Semantic Segmentation
C. Pose Estimation
D. Object Detection


12. What hardware should you use to calculate depth (Spatial AI)?

A. Eyecloud camera
B. NVIDIA Jetson Nano
C. Depth Cameras like the RealSense
D. Raspberry pi


13. What portion of the image does semantic segmentation assign labels to?

A. Every pixel
B. A range of pixels
C. the entire image
D. it assigns no labels


14. What edge devices are NOT supported on alwaysAI?

A. Production Cameras like NCC Knight
B. Raspberry Pi
C. NVIDIA NX Xavier
D. NVIDIA AGX Xavier


15. How do you add Python requirements to your application?

A. Add it on Requirement.Text
B. Add it to the Docker file
C. You can’t use extensions
D. NPM Install


Answer Key
A 2. B 3. A 4. D 5. C 6. A 7. A 8. B 9. C 10. B 11. D 12. C 13. A 14. D 15. A

Watch the full Hacky Hour video below. 

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By Komal Devjani Dec 28, 2020