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| from fastai.vision.all import load_learner | |
| import gradio as gr | |
| image_path = 'test_images' | |
| version = 1 | |
| # List of art forms | |
| art_labels = ('Art Deco', | |
| 'Art Nouveau', | |
| 'Avant-Garde', | |
| 'Bauhaus', | |
| 'Cubism', | |
| 'Dadaism', | |
| 'Futurism', | |
| 'Gothic Art', | |
| 'Hyperrealism', | |
| 'Impressionism', | |
| 'Minimalism', | |
| 'Neoclassicism Painting', | |
| 'Pop Art', | |
| 'Rococo', | |
| 'Surrealism') | |
| model = load_learner(f'model/art-recognizer-v{version}.pk1') | |
| def recognize_image(image): | |
| ored, idx, probs = model.predict(image) | |
| return dict(zip(art_labels, map(float,probs))) | |
| examples = [ | |
| f'data/{image_path}/318e97d070a64117b5f0e11d1b400ac0_sw-3598_sh-2864.png', | |
| f'data/{image_path}/55da4620b6a543a0b8911f6e3b3556e5_sw-2924_sh-2924.png', | |
| f'data/{image_path}/60c0bc4a8f8c4c7b823a2e521e9e92f1_sw-1280_sh-1277.png', | |
| f'data/{image_path}/6fbb1f7dd9a14dfc904ccdcdf38585cf_sw-4854_sh-6327.png', | |
| f'data/{image_path}/7ca2d0a2badf40c0a3ecbc11b1b9d9b7_sw-3568_sh-2873.png', | |
| f'data/{image_path}/a23cb16bb7d74c6ca0f82425dff83038_sw-2404_sh-3226.png', | |
| f'data/{image_path}/a3f0f15b5f8b4a81ab7b43ce7a7f010f_sw-1735_sh-2018.png', | |
| f'data/{image_path}/b05f56198e124b0b939a4833124ed120_sw-3032_sh-3084.png', | |
| f'data/{image_path}/ba504178173346a197bdd27c897cce0f_sw-700_sh-700.png', | |
| f'data/{image_path}/c356a06a48b8433a8849423baf100d76_sw-2189_sh-3349.png', | |
| f'data/{image_path}/c963c33c399d4591ad9184f62c40d595_sw-4751_sh-4794.png', | |
| f'data/{image_path}/d932a11b39d44846952c8f4ec4cc8d64_sw-1597_sh-1582.png', | |
| f'data/{image_path}/e1f7a31e434044138da27d13ba04a287_sw-1280_sh-1280.png', | |
| f'data/{image_path}/f97cb2052a80438eb1de81c81556f101_sw-3221_sh-4307.png' | |
| ] | |
| # Define your interface | |
| iface = gr.Interface( | |
| fn=recognize_image, | |
| inputs=gr.Image(type="filepath",width=200, height=200), | |
| outputs=gr.Label(), | |
| examples=examples | |
| ) | |
| iface.launch(inline=False) |