Upload app.py

app.py

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+#!/usr/bin/env python
+# -*- coding: utf-8 -*-
+"""
+🤖 Arabic OCR - Hugging Face Spaces Version
+Model: Qwen3.5-0.8B-VL with LoRA
+No Quantization - Full Precision
+"""
+
+import os
+import time
+import torch
+from PIL import Image
+import gradio as gr
+from transformers import AutoProcessor, Qwen3_5ForConditionalGeneration
+from qwen_vl_utils import process_vision_info
+
+# ==================== ⚙️ إعدادات الجهاز ====================
+if torch.cuda.is_available():
+    device = "cuda"
+    dtype = torch.float16
+    print(f"✅ Using GPU: {torch.cuda.get_device_name(0)}")
+elif torch.backends.mps.is_available():
+    device = "mps"
+    dtype = torch.float16
+    print("✅ Using Apple Silicon (MPS)")
+else:
+    device = "cpu"
+    dtype = torch.float32
+    print("⚠️ Using CPU (slower inference)")
+
+print(f"[INFO] Device: {device} | Dtype: {dtype}")
+
+# ==================== 🔄 تحميل النموذج ====================
+def load_model():
+    """تحميل النموذج والمعالج مع إدارة الذاكرة"""
+    model_path = os.getenv("MODEL_PATH", "./qwen3.5vl-08-7-42000")
+    
+    print(f"[INFO] Loading model from: {model_path}")
+    
+    processor = AutoProcessor.from_pretrained(model_path, trust_remote_code=True)
+    
+    model = Qwen3_5ForConditionalGeneration.from_pretrained(
+        model_path,
+        torch_dtype=dtype,
+        device_map="auto" if device == "cuda" else None,
+        trust_remote_code=True,
+        low_cpu_mem_usage=True,
+    )
+    
+    model.eval()
+    print("[INFO] Model loaded successfully!")
+    return model, processor
+
+# تحميل عالمي (يتم مرة واحدة عند بدء التطبيق)
+try:
+    model, processor = load_model()
+except Exception as e:
+    print(f"[ERROR] Failed to load model: {e}")
+    model = None
+    processor = None
+
+# ==================== 🧹 دوال مساعدة ====================
+def prepare_image(image: Image.Image, max_size: int = 768) -> Image.Image:
+    """تحضير الصورة: ضغط + ضبط الأبعاد لمضاعفات 64"""
+    if max(image.size) > max_size:
+        image.thumbnail((max_size, max_size), Image.Resampling.LANCZOS)
+    
+    w, h = image.size
+    new_w = ((w + 63) // 64) * 64
+    new_h = ((h + 63) // 64) * 64
+    if (new_w, new_h) != image.size:
+        image = image.resize((new_w, new_h), Image.Resampling.LANCZOS)
+    
+    return image
+
+def clean_output(text: str, max_repetitions: int = 2) -> str:
+    """تنظيف التكرار في المخرجات"""
+    if not text:
+        return text
+    
+    import re
+    text = re.sub(r'(.)\1{4,}', r'\1\1\1', text)
+    
+    lines = text.strip().split('\n')
+    cleaned = []
+    seen = {}
+    for line in lines:
+        line_stripped = line.strip()
+        if not line_stripped:
+            continue
+        count = seen.get(line_stripped, 0) + 1
+        if count <= max_repetitions:
+            cleaned.append(line)
+        seen[line_stripped] = count
+    
+    return '\n'.join(cleaned).strip()
+
+# ==================== 🔍 دالة الاستدلال ====================
+def extract_text(image, prompt: str = None) -> tuple[str, str]:
+    """استخراج النص من الصورة"""
+    if model is None or processor is None:
+        return "❌ Error: Model not loaded", "0.00"
+    
+    if image is None:
+        return "⚠️ Please upload an image", "0.00"
+    
+    start_time = time.time()
+    
+    try:
+        if isinstance(image, str):
+            image_pil = Image.open(image).convert("RGB")
+        elif isinstance(image, Image.Image):
+            image_pil = image.convert("RGB")
+        else:
+            image_pil = Image.fromarray(image).convert("RGB")
+        
+        image_pil = prepare_image(image_pil)
+        
+        if prompt is None or not prompt.strip():
+            prompt = "اقرأ النص في هذه الصورة كاملاً من البداية إلى النهاية."
+        
+        messages = [{
+            "role": "user",
+            "content": [
+                {"type": "image", "image": image_pil},
+                {"type": "text", "text": prompt}
+            ]
+        }]
+        
+        text_input = processor.apply_chat_template(
+            messages, tokenize=False, add_generation_prompt=True
+        )
+        image_inputs, _ = process_vision_info(messages)
+        
+        inputs = processor(
+            text=[text_input],
+            images=image_inputs,
+            padding=True,
+            return_tensors="pt"
+        ).to(device)
+        
+        with torch.inference_mode():
+            generated_ids = model.generate(
+                **inputs,
+                max_new_tokens=512,
+                do_sample=False,
+                temperature=1.0,
+                repetition_penalty=1.2,
+                no_repeat_ngram_size=3,
+                pad_token_id=processor.tokenizer.pad_token_id,
+                eos_token_id=processor.tokenizer.eos_token_id,
+            )
+        
+        input_len = inputs.input_ids.shape[1]
+        output_text = processor.batch_decode(
+            generated_ids[:, input_len:],
+            skip_special_tokens=True,
+            clean_up_tokenization_spaces=False
+        )[0]
+        
+        output_text = clean_output(output_text.strip())
+        
+        elapsed = time.time() - start_time
+        
+        return output_text, f"{elapsed:.2f} seconds"
+        
+    except torch.cuda.OutOfMemoryError:
+        torch.cuda.empty_cache()
+        return "❌ Out of Memory. Try a smaller image.", "0.00"
+    except Exception as e:
+        print(f"[ERROR] {e}")
+        import traceback
+        traceback.print_exc()
+        return f"❌ Error: {str(e)}", "0.00"
+
+# ==================== 🎨 واجهة Gradio ====================
+def create_interface():
+    """إنشاء واجهة المستخدم"""
+    
+    with gr.Blocks(
+        title="Arabic OCR - Qwen3.5-0.8B",
+        theme=gr.themes.Soft(),
+        css="""
+        .header { text-align: center; margin-bottom: 20px; }
+        .output-box { min-height: 200px; }
+        """
+    ) as demo:
+        
+        gr.Markdown("""
+        # 📝 Arabic Handwritten & Printed OCR V4
+        ### Powered by Qwen3.5-0.8B
+        
+        Upload an image containing Arabic text, and the model will extract it.
+        
+        ✨ **Features:**
+        - 🌍 Arabic support
+        - ✍️ Handwritten & printed text
+        - 🔤 Preserves diacritics (تشكيل)
+        - ⚡ Full precision (no quantization)
+        """, elem_classes="header")
+        
+        with gr.Row():
+            with gr.Column(scale=1):
+                # ✅ تعريف المكونات أولاً
+                image_input = gr.Image(
+                    label="📷 Upload Image",
+                    type="pil",
+                    height=300,
+                    sources=["upload", "clipboard"]
+                )
+                
+                prompt_input = gr.Textbox(
+                    label="📝 Custom Prompt (Optional)",
+                    placeholder="اقرأ النص في هذه الصورة...",
+                    value="اقرأ النص في هذه الصورة كاملاً من البداية إلى النهاية.",
+                    lines=2
+                )
+                
+                submit_btn = gr.Button(
+                    "🔍 Extract Text",
+                    variant="primary",
+                    size="lg"
+                )
+                
+                # ✅ الأمثلة داخل الدالة - مسارات محلية فقط (لا روابط خارجية)
+                # لإضافة أمثلة، انسخ الصور إلى مجلد 'examples/' في مستودع الـ Space
+                # ثم استخدم: examples=[["examples/sample1.jpg"], ...]
+                gr.Examples(
+                    label="📋 Examples (Optional)",
+                                examples=[
+                ["https://huggingface.co/sherif1313/Arabic-handwritten-OCR-4bit-Qwen2.5-VL-3B-v2/resolve/main/assets/00002.png"],
+                ["https://huggingface.co/sherif1313/Arabic-handwritten-OCR-4bit-Qwen2.5-VL-3B-v2/resolve/main/assets/00106.png"],
+                ["https://huggingface.co/sherif1313/Arabic-handwritten-OCR-4bit-Qwen2.5-VL-3B-v2/resolve/main/assets/00107.png"],
+                ["https://huggingface.co/sherif1313/Arabic-handwritten-OCR-4bit-Qwen2.5-VL-3B-v2/resolve/main/assets/00113.png"],
+                ["https://huggingface.co/sherif1313/Arabic-handwritten-OCR-4bit-Qwen2.5-VL-3B-v2/resolve/main/assets/00126.png"],
+                ["https://huggingface.co/sherif1313/Arabic-handwritten-OCR-4bit-Qwen2.5-VL-3B-v2/resolve/main/assets/00135.png"],
+                ["https://huggingface.co/sherif1313/Arabic-handwritten-OCR-4bit-Qwen2.5-VL-3B-v2/resolve/main/assets/00141.png"],
+                ["https://huggingface.co/sherif1313/Arabic-handwritten-OCR-4bit-Qwen2.5-VL-3B-v2/resolve/main/assets/00197.png"],
+                ["https://huggingface.co/sherif1313/Arabic-handwritten-OCR-4bit-Qwen2.5-VL-3B-v2/resolve/main/assets/00198.png"],
+                ["https://huggingface.co/sherif1313/Arabic-handwritten-OCR-4bit-Qwen2.5-VL-3B-v2/resolve/main/assets/00199.png"],
+                ["https://huggingface.co/sherif1313/Arabic-handwritten-OCR-4bit-Qwen2.5-VL-3B-v2/resolve/main/assets/00216.png"],
+                ["https://huggingface.co/sherif1313/Arabic-handwritten-OCR-4bit-Qwen2.5-VL-3B-v2/resolve/main/assets/00240.png"],
+            ],  # اتركها فارغة أو استخدم مسارات محلية
+                    inputs=[image_input],  # ✅ الآن يعمل لأن image_input مُعرّف أعلاه
+                    cache_examples=False
+                )
+                
+            with gr.Column(scale=1):
+                output_text = gr.Textbox(
+                    label="📄 Extracted Text",
+                    lines=12,
+                    show_copy_button=True,
+                    elem_classes="output-box"
+                )
+                
+                time_output = gr.Textbox(
+                    label="⏱️ Inference Time",
+                    interactive=False,
+                    value="-"
+                )
+                
+                clear_btn = gr.Button("🗑️ Clear", variant="secondary")
+        
+        # ✅ ربط الأحداث (بعد تعريف جميع المكونات)
+        submit_btn.click(
+            fn=extract_text,
+            inputs=[image_input, prompt_input],
+            outputs=[output_text, time_output]
+        )
+        
+        clear_btn.click(
+            fn=lambda: (None, "", "-"),
+            inputs=[],
+            outputs=[image_input, prompt_input, time_output]
+        )
+        
+        gr.Markdown("""
+        ### 💡 Tips for Best Results:
+        1. Use clear, well-lit images
+        2. Crop to the text region if possible
+        3. For handwritten text, ensure good contrast
+        4. Custom prompts can improve accuracy for specific formats
+        """)
+    
+    return demo  # ✅ إرجاع الـ demo
+
+# ==================== 🚀 نقطة الدخول ====================
+if __name__ == "__main__":
+    print("[INFO] Creating Gradio interface...")
+    
+    demo = create_interface()
+    
+    # إعدادات التشغيل لـ Spaces
+    demo.launch(
+        server_name="0.0.0.0",
+        server_port=int(os.getenv("PORT", 7860)),
+        share=False,
+        debug=os.getenv("DEBUG", "false").lower() == "true",
+        show_error=True
+    )