Parrot-Species-Classifier

An image classifier model that can classify 50 parrot species with 91% accuracy. Click here for live demo.

fast ai and resnet34 were used to predict images of 50 different parrot species.

The project goal was to build an image classification model and deploy it on the web that can successfully classify 50 different parrot species.

The types are following:

Species	Species	Species	Species	Species	Species
1. african grey parrot	11. caique parrot	21. golden parakeet	31. major mitchell_s cockatoo	41. red crowned parakeet	51. senegal parrot
2. australian king parrot	12. catalina macaw	22. great green macaw	32. monk parakeet	42. red fan parrot	52. spixs macaw
3. australian night parrot	13. chestnut-fronted macaw	23. great hanging parrot	33. musk lorikeet'	43. red lory	53. sulpher crested cockatoo
4. bare eyed cockatoo	14. citron cockatoo	24. greater vasa parrot	34. palm cockatoo	44. red rumped parrot	54. sun conure
5. blue and yellow macaw	15. cockatiels	25. hahn_s macaws	35. parrotlet	45. red shouldered macaw	55. thick billed parrot
6. blue headed parrot	16. crimson rosella	26. hooded parrot	36. plum headed parakeet	46. red tailed black cockatoos	56. turquoise fronted amazon
7. blue lorikeet	17. cuban amazon	27. hyacinth macaw	37. puerto rican amazon	47. rose ringed parakeett	57. umbrella cockatoo
8. brown hooded parrot	18. eclectus parro	28. kea	38. rainbow lorikeet	48. saint vincent amazon	58. vernal hanging parrot
9. budgerigar	19. galah cockatoo	29. kākāpō	39. red breasted parakeet	49. salmon crested cockatoo	59. yellow collared macaws
10. burrowing parrot	20. gang gang cockatoo	30. lovebirds	40. red crowned amazonn	50. scarlet macaw	60. yellow-headed amazon

Data collection & Dataset Preparation

Data Collection: The data was collected by downloading images from the web using each of the parrot class names from DuckDuckGo search of fastbook module DataLoader: fastai DataBlock API were used to set up the DataLoader and Resnet34 was used and later fine tuned multiple times. Data Augmentation: fastai provides default data augmentation which operates in GPU. Details can be found in notebooks/1_Parrots_classifier_data_prep.ipynb

Training and Data Cleaning

Training: Fine-tuned a resnet34 model for 5 epochs and got upto 91% accuracy. Data Cleaning: This part took the highest time. Since the collected data were from browser, there were many noises. Also, there were images that contained Animations, adds as well as there were garbage data that contains irrelevent subjects. I used the fastai ImageClassifierCleaner to clean and update the data. I cleaned the data after each training or finetuning iteration, except for the final iteration, which was the final version of the model.

Model Deployment

The final model was deployed in HuggingFace Spaces using Gradio App. The implementation can be found in deployment here

API integration with GitHub Pages

The deployed model API is integrated here in GitHub Pages Website. Implementation and other details can be found in the docs folder.