asdfsdffvd

app.py

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+import gradio as gr
+from fastai.vision.all import *
+import skimage
+
+training_set = "mane6-8000"
+
+
+# this is here, because it needs to be, otherwise I have no friggin clue
+def get_x(r): return os.path.join(training_set, r['fname'].replace('png', 'jpg').replace('gif', 'jpg').replace('svg', 'jpg')) # the replacing part is an interim solution lol (bug on a different end)
+def get_y(r): return r['tag']
+
+learn = load_learner('export.pkl') # pls rename
+
+labels = learn.dls.vocab
+def predict(img):
+    img = PILImage.create(img)
+    pred,pred_idx,probs = learn.predict(img)
+    return {labels[i]: float(probs[i]) for i in range(len(labels))}
+
+title = "Ember"
+description = ""
+examples = ["examples/1.jpg", "examples/2.jpg", "examples/3.jpg", "examples/4.jpg"]
+interpretation='default'
+enable_queue=True
+
+gr.Interface(
+    fn=predict,
+    inputs=gr.inputs.Image(shape=(400, 400)),
+    outputs=gr.outputs.Label(num_top_classes=3),
+    title=title,
+    description=description,
+    examples=examples,
+    interpretation=interpretation,
+    enable_queue=enable_queue).launch()
+
+"""
+LINKS
+https://tmabraham.github.io/blog/gradio_hf_spaces_tutorial
+"""

export.pkl

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+version https://git-lfs.github.com/spec/v1
+oid sha256:1e1445a693e8d0f1a0b277dc27d187c2839e3991c849c9d27512a9db3750ac30
+size 87514917

requirements.txt

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+fastai
+scikit-image