Create app.py

app.py

@@ -0,0 +1,29 @@
+import os
+import glob
+import requests
+import zipfile
+import torch
+from fastai.vision.all import *
+import gradio as gr
+from torchvision import transforms
+from PIL import Image
+
+
+# Load pretrained fastai Learner object
+learn = load_learner('model.pkl', cpu=True)
+
+# Used to convert prediction classes to text
+part_labels = ['chert1-2mm','obsidian1-2mm', 'soil2-4mm']
+
+def predict(inp):
+    """
+    Prediction for fast.ai fine tuned particle model
+    """
+    prediction = learn.predict(inp)[2]
+    confidences = {part_labels[i]: float(prediction[i]) for i in range(3)}
+    return confidences
+
+gr.Interface(fn=predict, 
+             inputs=gr.Image(type="numpy"),
+             outputs=gr.Label(num_top_classes=3),
+             examples=["Default-archeo_transparency_EXP00006-Obsidian-HH-2mm_20210504_131710(All particles)5300_57_05.bmp"]).launch()