| # # -*- coding: utf-8 -*- | |
| # """app creation.ipynb | |
| # Automatically generated by Colaboratory. | |
| # Original file is located at | |
| # https://colab.research.google.com/drive/1c8HIdMTAJxhNiPY7_kmzP78yFiwdhh8Q | |
| # """ | |
| # import gradio as gr | |
| # from fastai import * | |
| # from fastai.vision.all import * | |
| # # import pathlib | |
| # # temp = pathlib.PosixPath | |
| # # pathlib.PosixPath = pathlib.WindowsPath | |
| # model = load_learner("models/recgonizer_model.pkl") | |
| # labels = ['Ayre', 'Catla', 'Chital', 'Ilish', 'Kachki', 'Kajoli', 'Koi', 'Magur', 'Mola Dhela', 'Mrigal', 'Pabda', 'Pangash', 'Poa', 'Puti', 'Rui', 'Shing', 'Silver Carp', 'Taki', 'Telapia', 'Tengra'] | |
| # def recognize_image(image_path): | |
| # label, _, probs = model.predict(image_path) | |
| # return dict(zip(labels, map(float, probs))) | |
| # inputs = gr.inputs.Image(shape=(224,224)) | |
| # outputs = gr.outputs.Label() | |
| # examples = [ | |
| # 'test images/unknown_01.jpg', | |
| # 'test images/unknown_02.png', | |
| # 'test images/unknown_03.jpg', | |
| # 'test images/unknown_04.jpg', | |
| # 'test images/unknown_05.jpg', | |
| # 'test images/unknown_06.jpg', | |
| # 'test images/unknown_07.jpg', | |
| # 'test images/unknown_08.jpg', | |
| # 'test images/unknown_09.jpg', | |
| # 'test images/unknown_10.jpg', | |
| # 'test images/unknown_11.jpg', | |
| # 'test images/unknown_12.png', | |
| # 'test images/unknown_13.jpg', | |
| # 'test images/unknown_14.png', | |
| # 'test images/unknown_15.png', | |
| # 'test images/unknown_16.png', | |
| # 'test images/unknown_17.jpg' | |
| # ] | |
| # interface = gr.Interface(fn=recognize_image, inputs = inputs, outputs=outputs, examples = examples) | |
| # interface.launch() | |
| # -*- coding: utf-8 -*- | |
| """app creation.ipynb | |
| Automatically generated by Colaboratory. | |
| Original file is located at | |
| https://colab.research.google.com/drive/1c8HIdMTAJxhNiPY7_kmzP78yFiwdhh8Q | |
| """ | |
| import numpy as np | |
| import gradio as gr | |
| from fastai import * | |
| from fastai.vision.all import * | |
| import pathlib | |
| temp = pathlib.PosixPath | |
| pathlib.PosixPath = pathlib.WindowsPath | |
| model = load_learner("models/recgonizer_model.pkl") | |
| labels = ['Ayre', 'Catla', 'Chital', 'Ilish', 'Kachki', 'Kajoli', 'Koi', 'Magur', 'Mola Dhela', 'Mrigal', 'Pabda', 'Pangash', 'Poa', 'Puti', 'Rui', 'Shing', 'Silver Carp', 'Taki', 'Telapia', 'Tengra'] | |
| def recognize_image(image_path): | |
| label, _, probs = model.predict(image_path) | |
| # return dict(zip(labels, map(float, probs))) | |
| print(f"Category with most probability: {np.argmax(probs)}") | |
| return image_path, dict(zip(labels, map(float, probs))) | |
| # inputs = gr.inputs.Image(shape=(224,224)) | |
| # outputs = gr.outputs.Label() | |
| examples = [ | |
| 'test images/unknown_01.jpg', | |
| 'test images/unknown_02.png', | |
| 'test images/unknown_03.jpg', | |
| 'test images/unknown_04.jpg', | |
| 'test images/unknown_05.jpg', | |
| 'test images/unknown_06.jpg', | |
| 'test images/unknown_07.jpg', | |
| 'test images/unknown_08.jpg', | |
| 'test images/unknown_09.jpg', | |
| 'test images/unknown_10.jpg', | |
| 'test images/unknown_11.jpg', | |
| 'test images/unknown_12.png', | |
| 'test images/unknown_13.jpg', | |
| 'test images/unknown_14.png', | |
| 'test images/unknown_15.png', | |
| 'test images/unknown_16.png', | |
| 'test images/unknown_17.jpg' | |
| ] | |
| interface = gr.Interface(fn=recognize_image, inputs = gr.Image(), outputs = [gr.Image(height=224, width=224), gr.Label(num_top_classes=5)] , examples = examples) | |
| interface.launch() | |