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.gitattributes

@@ -33,3 +33,4 @@ saved_model/**/* filter=lfs diff=lfs merge=lfs -text
 *.zip filter=lfs diff=lfs merge=lfs -text
 *.zst filter=lfs diff=lfs merge=lfs -text
 *tfevents* filter=lfs diff=lfs merge=lfs -text
+wifi_basics_teaching_genspark.pdf filter=lfs diff=lfs merge=lfs -text

Dockerfile

@@ -0,0 +1,22 @@
+FROM python:3.10-slim
+
+# Install system dependencies
+RUN apt-get update && apt-get install -y \
+    poppler-utils \
+    libgl1 \
+    && rm -rf /var/lib/apt/lists/*
+
+# Set environment variables for HF Spaces
+ENV GRADIO_SERVER_NAME=0.0.0.0
+ENV GRADIO_SERVER_PORT=7860
+
+# Install Python packages
+COPY requirements.txt /tmp/requirements.txt
+RUN pip install --no-cache-dir -r /tmp/requirements.txt
+
+# Copy app code
+COPY . /app
+WORKDIR /app
+
+# Run your Gradio app (change as needed)
+CMD ["python", "app.py"]

app.py

@@ -0,0 +1,122 @@
+import gradio as gr
+import os
+import tempfile
+import numpy as np
+import cv2
+import img2pdf
+from pathlib import Path
+from pdf2image import convert_from_path # Make sure pdf2image is installed: pip install pdf2image opencv-python numpy img2pdf
+
+# Define a default bounding box (e.g., for a logo area)
+# Bounding box: (x1, y1, x2, y2) in fractions of image size
+default_bbox = (0.75, 0.9, 0.98, 0.98)
+
+def expand_bbox(bbox, expand_factor=0.3):
+    """Expands a bounding box by a given factor."""
+    x_min, y_min, x_max, y_max = bbox
+    width = x_max - x_min
+    height = y_max - y_min
+
+    new_x_min = max(0, x_min - width * expand_factor)
+    new_y_min = max(0, y_min - height * expand_factor)
+    new_x_max = min(1, x_max + width * expand_factor)
+    new_y_max = min(1, y_max + height * expand_factor)
+    return (new_x_min, new_y_min, new_x_max, new_y_max)
+
+def inpaint_image(image_np, bbox, color=(255, 255, 255)):
+    """
+    Inpaints a specified bounding box area in an image with a solid color.
+    image_np: NumPy array of the image (BGR format).
+    bbox: Tuple (x_min, y_min, x_max, y_max) in relative coordinates (0 to 1).
+    color: Tuple (B, G, R) for the inpaint color.
+    """
+    h, w, _ = image_np.shape
+    x1 = int(bbox[0] * w)
+    y1 = int(bbox[1] * h)
+    x2 = int(bbox[2] * w)
+    y2 = int(bbox[3] * h)
+
+    # Create a copy to avoid modifying the original image array directly
+    inpainted_image = image_np.copy()
+
+    # Fill the bounding box with the specified color
+    cv2.rectangle(inpainted_image, (x1, y1), (x2, y2), color, -1) # -1 fills the rectangle
+    return inpainted_image
+
+# --- End Placeholder functions ---
+
+
+def process_pdf(pdf_file):
+    """
+    Processes a PDF file, inpainting specified areas on each page.
+    """
+    try:
+        # Use test.pdf if nothing uploaded
+        # Ensure 'wifi_basics_teaching_genspark.pdf' exists in the same directory
+        # as your script for this to work when no file is uploaded.
+        pdf_path = pdf_file.name if pdf_file else "wifi_basics_teaching_genspark.pdf"
+        assert os.path.exists(pdf_path), f"File not found: {pdf_path}. Please upload a PDF or ensure 'wifi_basics_teaching_genspark.pdf' is in the current directory."
+
+        # Define inpaint colors per page
+        page_inpaint_colors = {
+            0: (255, 255, 255),  # white for page 0 (BGR)
+            1: (0, 0, 0)         # black for page 1 (BGR)
+        }
+
+        with tempfile.TemporaryDirectory() as tmpdir:
+            # Convert PDF pages to images
+            images = convert_from_path(pdf_path, dpi=300, output_folder=tmpdir, fmt="png")
+            output_images = []
+
+            for i, img in enumerate(images):
+                # Convert PIL RGB to OpenCV BGR
+                np_img = np.array(img)[:, :, ::-1]
+                # Expand the default bounding box for inpainting
+                bbox = expand_bbox(default_bbox, expand_factor=0.3)
+                # Get color for the current page, default to white if not specified
+                color = page_inpaint_colors.get(i, (255, 255, 255))
+                # Perform inpainting
+                inpainted = inpaint_image(np_img, bbox, color=color)
+
+                # Save the inpainted image
+                img_path = os.path.join(tmpdir, f"page_{i}.png")
+                cv2.imwrite(img_path, inpainted)
+                output_images.append(img_path)
+
+            # Convert inpainted images back to a single PDF
+            output_pdf = os.path.join(tmpdir, "inpainted_output.pdf")
+            # Sort images by path to ensure correct page order in the output PDF
+            with open(output_pdf, "wb") as f:
+                f.write(img2pdf.convert([Path(p) for p in sorted(output_images)]))
+
+            return output_pdf
+    except Exception as e:
+        print(f"❌ Error during PDF processing: {e}")
+        # Return None to indicate an error, which safe_process_wrapper will handle
+        return None
+
+# Gradio app UI
+with gr.Blocks() as demo:
+    gr.Markdown("### 🧽 PDF Logo Inpainting (Solid Fill, Expand + Color Config)")
+    with gr.Row():
+        # Input component for PDF upload
+        pdf_input = gr.File(
+            label="Upload PDF (or leave empty to use test.pdf)",
+            file_types=[".pdf"],
+            interactive=True
+        )
+        # Output component for the processed PDF
+        pdf_output = gr.File(label="Download Inpainted PDF")
+
+    # Button to trigger the processing
+    run_button = gr.Button("Process and Inpaint")
+
+    # Link the button click to the processing function
+    run_button.click(
+        fn=process_pdf,
+        inputs=pdf_input,
+        outputs=pdf_output
+    )
+
+# Launch the Gradio application
+demo.launch()

requirements.txt

@@ -0,0 +1,4 @@
+gradio
+pdf2image
+opencv-python
+img2pdf

wifi_basics_teaching_genspark.pdf

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:fe6b2814b874daf0a0a8caadd73c8dff25e4b4dcdbfa5d9044e08b0f9c02ccd2
+size 7902815