| import gradio as gr | |
| from fastai.vision.all import load_learner | |
| nlearn = load_learner('./Ey.pkl') | |
| categories = ('Chennai', 'London') | |
| def classify_img(img): | |
| pred, idx, prob = nlearn.predict(img) | |
| return dict(zip(categories, map(float, prob))) | |
| def greet(name): | |
| return "Hello " + name + "!!" | |
| # classify_img('/kaggle/input/help-me/Screenshot 2024-02-08 at 23.19.37.png') | |
| image = gr.Image(height=192,width=192) | |
| label = gr.Label() | |
| desc = "This model classifies satellite image of a particular area into possible cities. right now this is trained with Chennai and London city images" | |
| examples = ['./test_data/chennai_1.png', './test_data/chennai_2.png', './test_data/chennai_3.png', './test_data/london_1.png', './test_data/chennai_1.png'] | |
| intf = gr.Interface(fn=classify_img, inputs=image, outputs=label, examples=examples, description=desc) | |
| intf.launch() | |
| # iface = gr.Interface(fn=greet, inputs="text", outputs="text") | |
| # iface.launch() | |