Added app.py and example images

README.md

@@ -1,6 +1,6 @@
 ---
 title: Bhl Clip Classifier
-emoji: 🐨
+emoji: 🍂
 colorFrom: green
 colorTo: gray
 sdk: gradio

app.py

@@ -0,0 +1,38 @@
+import gradio as gr
+from transformers import pipeline
+import numpy as np
+from PIL import Image
+
+checkpoint = "openai/clip-vit-base-patch32"
+classifier = pipeline(model=checkpoint, 
+                      task="zero-shot-image-classification")
+
+def shot(image, labels_text):
+    labels = labels_text.split(";")
+    results = classifier(image,
+                         candidate_labels=labels)
+    return {result["label"]: result["score"] for result in results}
+    
+demo = gr.Interface(shot, 
+                    [gr.Image(type="pil"), 
+                    gr.Textbox(
+                        label="Labels",
+                        info="Separated by a semicolon (;)",
+                        lines=6,
+                        value="""A page of printed text; 
+A page of handwritten text;
+A blank page with no text;
+A cover of a book;
+A page of a book that contains a large illustration;
+A page that features a table with multiple columns and rows""",
+                    )], 
+                    outputs="label", 
+                    examples=[['Journalsdateboo00DeanZ_0177.jpg',None], 
+                              ["newmexicobotani00newmb_0084.jpg",None],
+                              ["easternareacrui00natic_0004.jpg",None],
+                              ["newmexicobotani00newmb_0084.jpg",None],
+                              ["sturmsfiguresofp01stur_0263.jpg",None]],
+                    description="Upload an image of a scanned document page, or choose one of the examples below",
+                    title="Zero-shot Image Classification of BHL Images")
+
+demo.launch()

requirements.txt

@@ -0,0 +1,4 @@
+torch
+transformers
+pillow
+numpy