feat: add Gradio app for ZeroGPU

README.md

@@ -3,9 +3,9 @@ title: Manga Translator
 emoji: 📚
 colorFrom: pink
 colorTo: purple
-sdk: streamlit
-sdk_version: 1.40.0
-app_file: app.py
+sdk: gradio
+sdk_version: 4.28.3
+app_file: gradio_app.py
 pinned: false
 license: mit
 ---
@@ -46,7 +46,7 @@ Best option – provides **16 GB RAM** for free, which is needed for the OCR mod
 
 1.  Go to **[huggingface.co/spaces](https://huggingface.co/spaces)**
 2.  Click **"Create new Space"**
-3.  Select **Streamlit** as SDK
+3.  Select **Gradio** as SDK
 4.  Clone this repo or link your GitHub repo
 5.  The app will auto-deploy using the YAML header in this README
 

gradio_app.py

@@ -0,0 +1,255 @@
+import os
+import tempfile
+from typing import List, Optional
+
+import certifi
+import gradio as gr
+from PIL import Image
+
+from src.pdf_handler import PDFHandler
+from src.ocr_handler import OCRHandler
+from src.translator import TranslatorService
+from src.image_processor import ImageProcessor
+
+# Fix SSL issues for HTTPS APIs (DeepL / OpenAI / xAI)
+os.environ["SSL_CERT_FILE"] = certifi.where()
+
+pdf_handler = PDFHandler()
+image_processor = ImageProcessor()
+
+
+def parse_page_range(range_str: str) -> List[int]:
+    """Parse a page range string (e.g., "1-3, 5, 7-9") into a list of 0-indexed integers."""
+    if not range_str or not range_str.strip():
+        return []
+
+    pages: List[int] = []
+    parts = [p.strip() for p in range_str.split(",") if p.strip()]
+    for part in parts:
+        if "-" in part:
+            start_str, end_str = part.split("-", 1)
+            try:
+                start = int(start_str)
+                end = int(end_str)
+            except ValueError:
+                continue
+            if start > end:
+                start, end = end, start
+            pages.extend(list(range(start, end + 1)))
+        else:
+            try:
+                pages.append(int(part))
+            except ValueError:
+                continue
+
+    unique_pages = sorted(set(p for p in pages if p > 0))
+    return [p - 1 for p in unique_pages]
+
+
+def _build_translator(service_label: str, deepl_key: str, openai_key: str, xai_key: str) -> TranslatorService:
+    label_map = {
+        "Google Translate": "google",
+        "DeepL": "deepl",
+        "OpenAI GPT-4o-mini": "openai",
+        "xAI Grok": "xai",
+    }
+    service_type = label_map.get(service_label, "google")
+
+    api_key: Optional[str] = None
+    if service_type == "deepl":
+        api_key = deepl_key or None
+    elif service_type == "openai":
+        api_key = openai_key or None
+    elif service_type == "xai":
+        api_key = xai_key or None
+
+    if service_type in ["deepl", "openai", "xai"] and not api_key:
+        raise ValueError(f"Missing API key for {service_type} service.")
+
+    return TranslatorService(source="en", target="de", service_type=service_type, api_key=api_key)
+
+
+def translate_manga(
+    pdf_path: str,
+    page_range: str,
+    ocr_engine: str,
+    bubble_threshold: float,
+    preprocess_mode: str,
+    translator_label: str,
+    deepl_key: str,
+    openai_key: str,
+    xai_key: str,
+    show_boxes: bool,
+    use_vision: bool,
+):
+    if not pdf_path:
+        return None, [], "Bitte eine PDF-Datei hochladen."
+
+    try:
+        pages = parse_page_range(page_range)
+    except Exception:
+        pages = []
+
+    if not pages:
+        pages = None
+
+    translator = _build_translator(translator_label, deepl_key, openai_key, xai_key)
+
+    ocr_handler: Optional[OCRHandler] = None
+    if not use_vision:
+        # On ZeroGPU we can safely enable GPU acceleration
+        ocr_handler = OCRHandler(lang_list=["en"], gpu=True, ocr_engine=ocr_engine)
+
+    progress = gr.Progress(track_tqdm=True)
+
+    progress(0.0, desc="PDF wird geladen und in Bilder umgewandelt...")
+    images: List[Image.Image] = pdf_handler.extract_images_from_pdf(pdf_path, zoom=1.5, pages=pages)
+    total = len(images)
+    if total == 0:
+        return None, [], "Keine Seiten im PDF gefunden."
+
+    processed_images: List[Image.Image] = []
+
+    for idx, img in enumerate(images):
+        progress((idx / total), desc=f"Verarbeite Seite {idx + 1} von {total}...")
+
+        text_regions = []
+
+        if use_vision:
+            vision_results = translator.translate_image_with_vision(img)
+            for item in vision_results:
+                bbox = item["bbox"]
+                original = item.get("original", "")
+                translated = item.get("translated", "")
+                text_regions.append((bbox, original, translated))
+        else:
+            ocr_results = ocr_handler.detect_and_group_text(
+                img,
+                distance_threshold=bubble_threshold,
+                preprocess_mode=preprocess_mode,
+            )
+            for bbox, text in ocr_results:
+                if len(text.strip()) < 2:
+                    continue
+                translated_text = translator.translate_text(text)
+                text_regions.append((bbox, text, translated_text))
+
+        if show_boxes:
+            processed = image_processor.draw_boxes_only(img.copy(), text_regions)
+        else:
+            processed = image_processor.overlay_text(img.copy(), text_regions)
+
+        processed_images.append(processed)
+
+    tmp_dir = tempfile.mkdtemp(prefix="mangatranslator_")
+    output_pdf_path = os.path.join(tmp_dir, "translated_manga.pdf")
+
+    pdf_handler.save_images_as_pdf(processed_images, output_pdf_path)
+
+    progress(1.0, desc="Fertig!")
+
+    return output_pdf_path, processed_images, "Fertig! Du kannst das übersetzte PDF herunterladen."
+
+
+with gr.Blocks() as demo:
+    gr.Markdown("# 📚 Manga Translator (Gradio + ZeroGPU)")
+    gr.Markdown(
+        "Lädt ein Manga-PDF, erkennt Sprechblasen per OCR und legt die deutsche Übersetzung in die Sprechblasen."
+    )
+
+    with gr.Row():
+        with gr.Column():
+            pdf_input = gr.File(
+                label="Manga PDF hochladen",
+                file_types=[".pdf"],
+                type="filepath",
+            )
+            page_range = gr.Textbox(
+                label="Seitenbereich (optional)",
+                placeholder="z.B. 1-5, 7, 10-12 (leer = alle Seiten)",
+            )
+
+            ocr_engine = gr.Radio(
+                label="OCR-Engine",
+                choices=["magi", "manga-ocr", "paddleocr", "easyocr"],
+                value="magi",
+            )
+            preprocess_mode = gr.Radio(
+                label="OCR Preprocessing",
+                choices=["gentle", "none", "aggressive"],
+                value="gentle",
+            )
+            bubble_threshold = gr.Slider(
+                label="Bubble-Gruppierung (Pixel)",
+                minimum=20,
+                maximum=200,
+                value=80,
+                step=5,
+            )
+            show_boxes = gr.Checkbox(
+                label="Nur Boxen zeichnen (Debug)",
+                value=False,
+            )
+
+        with gr.Column():
+            translator_label = gr.Radio(
+                label="Übersetzungsdienst",
+                choices=[
+                    "Google Translate",
+                    "DeepL",
+                    "OpenAI GPT-4o-mini",
+                    "xAI Grok",
+                ],
+                value="Google Translate",
+            )
+            use_vision = gr.Checkbox(
+                label="Vision-Modus (OpenAI/xAI Vision)",
+                value=False,
+            )
+            deepl_key = gr.Textbox(
+                label="DeepL API Key",
+                type="password",
+                visible=True,
+            )
+            openai_key = gr.Textbox(
+                label="OpenAI API Key",
+                type="password",
+                visible=True,
+            )
+            xai_key = gr.Textbox(
+                label="xAI API Key",
+                type="password",
+                visible=True,
+            )
+
+            run_btn = gr.Button("🚀 Übersetzen")
+
+    output_pdf = gr.File(label="Übersetztes PDF")
+    preview_gallery = gr.Gallery(
+        label="Vorschau der verarbeiteten Seiten",
+        columns=3,
+        height="auto",
+    )
+    status_box = gr.Textbox(label="Status", interactive=False)
+
+    run_btn.click(
+        fn=translate_manga,
+        inputs=[
+            pdf_input,
+            page_range,
+            ocr_engine,
+            bubble_threshold,
+            preprocess_mode,
+            translator_label,
+            deepl_key,
+            openai_key,
+            xai_key,
+            show_boxes,
+            use_vision,
+        ],
+        outputs=[output_pdf, preview_gallery, status_box],
+    )
+
+
+if __name__ == "__main__":
+    demo.launch()