Update app.py

app.py

@@ -1,15 +1,25 @@
 import gradio as gr
-import pytesseract
+from PIL import Image
+from transformers import pipeline, AutoModelForVision2Seq, AutoProcessor
+import torch
 
+# Load the OpenGVLab/InternVL-Chat-V1-5 model and processor
+from transformers import AutoModel
+model = AutoModel.from_pretrained("OpenGVLab/InternVL-Chat-V1-5", trust_remote_code=True)
 
-#pytesseract.pytesseract.tesseract_cmd = r'/usr/bin/tesseract'
+# Load the Llama3 model for text processing
+#llama_model = pipeline("text2text-generation", model="llama3")
 
-def process_recipe(i,j):
-    text = pytesseract.image_to_string(Image.open(image))
-    return text
+def process_image(image):
+    # Process the image to extract the recipe using OpenGVLab
+    inputs = processor(images=image, return_tensors="pt")
+    generated_ids = model.generate(**inputs)
+    extracted_text = processor.batch_decode(generated_ids, skip_special_tokens=True)[0]
+
+    return extracted_text   
     
 iface = gr.Interface(
-    fn=process_recipe,
+    fn=process_image,
     inputs=[
         gr.components.Image(type="filepath", label="Recipe Image"),
         gr.components.Radio(choices=["Double","Triple", "Half", "Third"], label="Action")