First Commit

README.md

@@ -1,14 +1,18 @@
----
-title: Easy OCR
-emoji: 🔥
-colorFrom: green
-colorTo: pink
-sdk: gradio
-sdk_version: 5.34.1
-app_file: app.py
-pinned: false
-license: apache-2.0
-short_description: GPU-Accelerated OCR
----
-
-Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference
+# ZeroGPU OCR PDF Extractor
+
+**Key features**
+
+* ⚡️ *On‑demand GPU* — the `@spaces.GPU` decorator grabs a GPU only while OCR is running. Perfect for HuggingFace **ZeroGPU** Spaces.
+* 📝 Combines native PDF text (via **pdfplumber**) with OCR from images (via **EasyOCR**).
+* 🌍 Multilingual: add language codes to the `LANGS` list in `app.py`.
+
+## Deploy
+
+1. Create a *Gradio* Space and pick **ZeroGPU** in the **Hardware** dropdown (requires a PRO subscription).
+2. Upload these files or the ZIP bundle.
+3. Commit — the Space will build automatically. The first call downloads EasyOCR model weights (~200 MB).
+
+## Usage Tips
+
+* Large PDFs can take several minutes; the decorator is set to `duration=600` s. Adjust if needed.
+* For faster queues, lower the duration if your documents are small.

app.py

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+
+"""
+ZeroGPU‑ready OCR PDF extractor for HuggingFace Spaces
+-----------------------------------------------------
+• Uses @spaces.GPU to request a GPU only while needed (ZeroGPU compatible)
+• Extracts native text with `pdfplumber`
+• Runs GPU‑accelerated OCR on page images with `EasyOCR`
+"""
+
+import gradio as gr
+import fitz  # PyMuPDF
+import pdfplumber
+import easyocr
+import torch
+import tempfile
+import os
+import spaces  # <-- ZeroGPU decorator
+
+# Global reader object (lazy‑loaded after GPU is allocated)
+READER = None
+LANGS = ['en']  # add more language codes as desired
+
+@spaces.GPU(duration=600)  # request a GPU for up to 10 min per call
+def extract_text(pdf_file):
+    """Extract text (native + OCR) from an uploaded PDF"""
+    global READER
+
+    # Initialise EasyOCR reader after GPU becomes available
+    if READER is None:
+        READER = easyocr.Reader(LANGS, gpu=torch.cuda.is_available())
+
+    native_chunks = []
+    ocr_chunks = []
+
+    # Pass 1 — native text via pdfplumber
+    with pdfplumber.open(pdf_file.name) as pdf:
+        for idx, page in enumerate(pdf.pages, start=1):
+            txt = page.extract_text() or ""
+            if txt.strip():
+                native_chunks.append(f"--- Page {idx} (native) ---\n{txt}\n")
+
+    # Pass 2 — OCR each rendered page image with PyMuPDF + EasyOCR
+    doc = fitz.open(pdf_file.name)
+    for idx, page in enumerate(doc, start=1):
+        # Render page image at ~300 dpi
+        pix = page.get_pixmap(matrix=fitz.Matrix(2, 2))
+        tmp_path = os.path.join(tempfile.gettempdir(), f"page_{idx}.png")
+        pix.save(tmp_path)
+
+        ocr_result = READER.readtext(tmp_path, detail=0)
+        os.remove(tmp_path)
+
+        if any(line.strip() for line in ocr_result):
+            ocr_text = "\n".join(ocr_result)
+            ocr_chunks.append(f"--- Page {idx} (OCR) ---\n{ocr_text}\n")
+
+    combined = "\n".join(native_chunks + ocr_chunks)
+    return combined or "⚠️ No text detected in the document."
+
+DESCRIPTION = (
+    "Drop a PDF to extract **all** text. "
+    "Native PDF text is captured first; any remaining text in images is "
+    "recognized using EasyOCR. On ZeroGPU hardware, the app requests a "
+    "GPU *only* while OCR is running."
+)
+
+iface = gr.Interface(
+    fn=extract_text,
+    inputs=gr.File(label="Upload PDF"),
+    outputs=gr.Textbox(label="Extracted Text", show_copy_button=True),
+    title="ZeroGPU OCR PDF Extractor",
+    description=DESCRIPTION,
+    allow_flagging="never",
+    examples=None,
+    theme="default",
+)
+
+if __name__ == "__main__":
+    iface.launch()

requirements.txt

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+gradio>=4.0
+easyocr>=1.7.1
+torch>=2.0
+pdfplumber>=0.10.3
+PyMuPDF>=1.23.9
+spaces