from fastai.vision.all import * | |
import gradio as gr | |
import timm | |
import dill | |
import os | |
learn = load_learner('./models/catan-model-paperspace-5.pkl', pickle_module=dill) | |
# learn = load_learner('catan-model.pkl', pickle_module=dill) | |
# categories = learn.dls.vocab | |
categories = ('Not Catan', 'Catan') | |
def classify_image(img): | |
pred, idx, probs = learn.predict(img) | |
return dict(zip(categories, map(float, probs))) | |
# Cell | |
image = gr.inputs.Image(shape=(192, 192)) | |
label = gr.outputs.Label() | |
examples_dir_path = './examples/' | |
examples = [(examples_dir_path + filename) for filename in os.listdir(examples_dir_path) if filename[:1] != '.'] | |
# Cell | |
intf = gr.Interface(fn=classify_image, inputs=image, outputs=label, examples=examples) | |
intf.launch() | |