Goal is to build a pipeline that can be used within a web or mobile app to process real-world, user-supplied images. In this specific workload, the algorithm will be approximating the breed of a canine within a given image. If supplied an image of a human, the code will identify the resembling dog breed.
Dec. 10, 2020 Update:
- The app is deployed and available for user inputs. Please feel free to try the app via https://jiae.ai
- Next step: present the actual dog image that is detected.
Left image is my Chihuahua. My model has never seen the image, and yet, it matched the breed!
To the right is me, in which the model detects my face as human and matches my appearance with a dog breed, Lowchen!
By utilizing the techniques, including Transfer Learning, building a Convolutional Neural Network(CNN), auto-encoders and object detection, this project will explore the possibilities of CNN models in classification and localization, as well as engineering different models together to yield optimal results in specified tasks and user-experiences.
Here is a little cute puppy I met in S. Korea. How cute!
- dog image dataset.
- The unzipped,
dogImages/folder should contain 133 folders, each corresponding to a different dog breed.
- The unzipped,
- human face dataset.
- 7zip is recommended for extracting the folder, if Windows machine is used.