Create app.py

app.py

@@ -0,0 +1,57 @@
+import os
+import gradio as gr
+from PIL import Image
+from transformers import AutoProcessor, AutoModelForCausalLM 
+
+#workaround for unnecessary flash_attn requirement
+from unittest.mock import patch
+from transformers.dynamic_module_utils import get_imports
+import numpy as np
+
+def fixed_get_imports(filename: str | os.PathLike) -> list[str]:
+    if not str(filename).endswith("modeling_florence2.py"):
+        return get_imports(filename)
+    imports = get_imports(filename)
+    imports.remove("flash_attn")
+    return imports
+
+with patch("transformers.dynamic_module_utils.get_imports", fixed_get_imports): #workaround for unnecessary flash_attn requirement
+    model = AutoModelForCausalLM.from_pretrained("Oysiyl/Florence-2-FT-OCR-Cauldron-IAM", attn_implementation="sdpa", trust_remote_code=True)
+
+processor = AutoProcessor.from_pretrained("Oysiyl/Florence-2-FT-OCR-Cauldron-IAM", trust_remote_code=True)
+
+prompt = "OCR"
+
+
+def predict(im):
+    composite_image = Image.fromarray(im['composite'].astype(np.uint8)).convert("RGBA")
+    background_image = Image.new("RGBA", composite_image.size, (255, 255, 255, 255))
+    image = Image.alpha_composite(background_image, composite_image).convert("RGB")
+    inputs = processor(text=prompt, images=image, return_tensors="pt")
+
+    generated_ids = model.generate(
+        input_ids=inputs["input_ids"],
+        pixel_values=inputs["pixel_values"],
+        max_new_tokens=1024,
+        do_sample=False,
+        num_beams=3
+    )
+    generated_text = processor.batch_decode(generated_ids, skip_special_tokens=False)[0]
+
+    parsed_answer = processor.post_process_generation(generated_text, task=prompt, image_size=(image.width, image.height))
+
+
+    return parsed_answer[prompt]
+
+
+sketchpad = gr.ImageEditor(label="Draw something or upload an image")
+
+interface = gr.Interface(
+    predict,
+    inputs=sketchpad, 
+    outputs='text',
+    theme='gradio/monochrome',
+    title="Handwritten Recognition using Florence 2 model finetuned on IAM subset from HuggingFace Cauldron dataset", 
+    description="<p style='text-align: center'>Draw a text or upload an image with handwritten notes and let's model try to guess the text!</p>", 
+    article = "<p style='text-align: center'>Handwritten Text Recognition | Demo Model</p>")
+interface.launch(debug=True)