Create app.py

app.py

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+from transformers import Pix2StructProcessor, Pix2StructForConditionalGeneration
+import requests
+from PIL import Image
+
+processor = Pix2StructProcessor.from_pretrained('google/deplot')
+model = Pix2StructForConditionalGeneration.from_pretrained('google/deplot')
+
+url = "https://raw.githubusercontent.com/vis-nlp/ChartQA/main/ChartQA%20Dataset/val/png/5090.png"
+image = Image.open(requests.get(url, stream=True).raw)
+
+inputs = processor(images=image, text="Generate underlying data table of the figure below:", return_tensors="pt")
+predictions = model.generate(**inputs, max_new_tokens=512)
+print(processor.decode(predictions[0], skip_special_tokens=True))