displaying example output + slide images

end-to-end-use-cases/powerpoint-to-voiceover-transcript/README.md

@@ -12,6 +12,7 @@ This system extracts speaker notes and visual content from PowerPoint files, the
 - **Unified Processing**: Single processor handles both standard and narrative-aware modes
 - **Narrative Continuity**: Optional context-aware processing maintains smooth transitions
 - **Speech Optimization**: Converts numbers, decimals, and technical terms to spoken form
+- **Visualization Tools**: Built-in utilities for displaying slide images in Jupyter notebooks
 - **Flexible Configuration**: Toggle between processing modes with simple flags
 - **Cross-Platform**: Works on Windows, macOS, and Linux
 - **Production Ready**: Comprehensive error handling, progress tracking, and retry logic
@@ -123,6 +124,7 @@ powerpoint-to-voiceover-transcript/
 ├── narrative_continuity_workflow.ipynb # Narrative-aware workflow
 ├── .env.example                       # Environment template
 ├── input/                             # Place your PPTX files here
+├── output/                            # Generated images and transcripts
 └── src/
     ├── config/
     │   └── settings.py                # Configuration management
@@ -131,8 +133,10 @@ powerpoint-to-voiceover-transcript/
     │   ├── image_processing.py        # Image encoding for API
     │   ├── llama_client.py            # Llama API integration
     │   └── pptx_processor.py          # PPTX extraction and conversion
-    └── processors/
-        └── unified_transcript_generator.py # Unified processor (standard + narrative)
+    ├── processors/
+    │   └── unified_transcript_generator.py # Unified processor (standard + narrative)
+    └── utils/
+        └── visualization.py           # Slide image display utilities
 ```
 
 ## Configuration
@@ -190,6 +194,30 @@ Main class for generating AI transcripts with configurable processing modes.
 - **Features**: Context awareness, smooth transitions, terminology consistency
 - **Use cases**: Conference talks, educational courses, marketing presentations
 
+### Visualization Utilities
+
+#### `display_slide_grid(image_files, max_cols=3, figsize_per_image=(4, 3))`
+Display slide images in a grid layout for Jupyter notebooks.
+
+**Parameters:**
+- `image_files` (List): List of image file paths
+- `max_cols` (int): Maximum columns in grid (default: 3)
+- `figsize_per_image` (Tuple): Size of each image as (width, height) (default: (4, 3))
+
+**Example:**
+```python
+from src.utils.visualization import display_slide_grid, display_slide_preview
+
+# Display first 6 slides in a 3-column grid
+display_slide_grid(image_files[:6], max_cols=3, figsize_per_image=(4, 3))
+
+# Or use the convenience function
+display_slide_preview(image_files, num_slides=6, max_cols=3)
+```
+
+#### `display_slide_preview(image_files, num_slides=6, max_cols=3, figsize_per_image=(4, 3))`
+Display a preview of the first N slide images with automatic grid layout.
+
 ### Legacy Functions (Backward Compatibility)
 
 #### `process_slides(df, output_dir, use_narrative=False)`
@@ -220,6 +248,7 @@ The AI automatically converts technical content for natural speech:
 - `llama-api-client>=0.1.0` - AI model access
 - `pillow>=11.3.0` - Image processing
 - `pyyaml>=6.0.0` - Configuration management
+- `matplotlib>=3.5.0` - Visualization utilities
 
 See `pyproject.toml` for complete dependency list.
 
@@ -233,6 +262,7 @@ Enhanced output includes:
 3. **Narrative Summary**: Overall analysis of presentation flow and consistency
 4. **Multiple Formats**: CSV, JSON exports with context information
 5. **Context Files**: Detailed narrative context data for each slide
+6. **Visual Preview**: Grid display of slide images for verification
 
 ## Troubleshooting
 
@@ -258,4 +288,9 @@ Enhanced output includes:
 - Reduce `context_window_size` parameter in narrative workflow
 - Default is 5 slides, try 3 for shorter presentations
 
----
+**"Images not displaying in notebook"**
+- Ensure matplotlib is installed: `pip install matplotlib`
+- Check that image files exist in the output directory
+- Try restarting the Jupyter kernel
+
+---

end-to-end-use-cases/powerpoint-to-voiceover-transcript/config.yaml

@@ -86,6 +86,7 @@ system_prompt: |
      - Is suitable for a 1.5–3 minute spoken video.
 
   4. Ensure the transcript:
+     - Does not contain the title of the slide.
      - Flows logically, even if slide layout is fragmented.
      - Expands acronyms or technical terms on first use (e.g., "LLM" becomes "Large Language Model, or LLM").
      - Maintains a neutral, respectful, and professional tone appropriate for stakeholders.

end-to-end-use-cases/powerpoint-to-voiceover-transcript/pyproject.toml

@@ -13,4 +13,5 @@ dependencies = [
     "tqdm>=4.66.0",
     "llama-api-client>=0.1.0",
     "pyyaml>=6.0.0",
+    "matplotlib>=3.10.5",
 ]

end-to-end-use-cases/powerpoint-to-voiceover-transcript/src/__init__.py

@@ -11,12 +11,18 @@ __version__ = "0.1.0"
 __author__ = "Yuce Dincer"
 
 from .core.pptx_processor import extract_pptx_notes, pptx_to_images_and_notes
-from .processors.transcript_generator import process_slides
+from .processors.unified_transcript_generator import (
+    UnifiedTranscriptProcessor,
+    process_slides,
+    process_slides_with_narrative
+)
 from .config.settings import load_config
 
 __all__ = [
     "extract_pptx_notes",
     "pptx_to_images_and_notes",
+    "UnifiedTranscriptProcessor",
     "process_slides",
+    "process_slides_with_narrative",
     "load_config"
 ]

end-to-end-use-cases/powerpoint-to-voiceover-transcript/src/processors/__init__.py

@@ -1,5 +1,13 @@
 """Processing modules for PPTX to Transcript."""
 
-from .transcript_generator import process_slides, TranscriptProcessor
+from .unified_transcript_generator import (
+    UnifiedTranscriptProcessor,
+    process_slides,
+    process_slides_with_narrative
+)
 
-__all__ = ["process_slides", "TranscriptProcessor"]
+__all__ = [
+    "UnifiedTranscriptProcessor",
+    "process_slides",
+    "process_slides_with_narrative"
+]

end-to-end-use-cases/powerpoint-to-voiceover-transcript/src/utils/__init__.py

@@ -0,0 +1,5 @@
+"""Utility functions for PPTX to Transcript."""
+
+from .visualization import display_slide_grid
+
+__all__ = ["display_slide_grid"]

end-to-end-use-cases/powerpoint-to-voiceover-transcript/src/utils/visualization.py

@@ -0,0 +1,105 @@
+"""Visualization utilities for displaying slide images and analysis results."""
+
+import matplotlib.pyplot as plt
+from PIL import Image
+import math
+from typing import List, Union, Tuple
+from pathlib import Path
+
+
+def display_slide_grid(
+    image_files: List[Union[str, Path]],
+    max_cols: int = 3,
+    figsize_per_image: Tuple[int, int] = (4, 3)
+) -> None:
+    """
+    Display slide images in a grid layout for Jupyter notebooks.
+
+    Args:
+        image_files: List of image file paths
+        max_cols: Maximum number of columns in the grid (default: 3)
+        figsize_per_image: Size of each image subplot as (width, height) (default: (4, 3))
+
+    Example:
+        # Display first 6 slides in a 3-column grid
+        display_slide_grid(image_files[:6], max_cols=3, figsize_per_image=(4, 3))
+
+        # Display all slides in a 2-column grid with larger images
+        display_slide_grid(image_files, max_cols=2, figsize_per_image=(6, 4))
+    """
+    if not image_files:
+        print("No images to display")
+        return
+
+    num_images = len(image_files)
+    cols = min(max_cols, num_images)
+    rows = math.ceil(num_images / cols)
+
+    # Calculate figure size
+    fig_width = cols * figsize_per_image[0]
+    fig_height = rows * figsize_per_image[1]
+
+    fig, axes = plt.subplots(rows, cols, figsize=(fig_width, fig_height))
+
+    # Handle single row/column cases
+    if rows == 1 and cols == 1:
+        axes = [axes]
+    elif rows == 1 or cols == 1:
+        axes = axes.flatten()
+    else:
+        axes = axes.flatten()
+
+    for i, img_path in enumerate(image_files):
+        try:
+            # Load and display image
+            img = Image.open(img_path)
+            axes[i].imshow(img)
+            axes[i].set_title(f"Slide {i+1}", fontsize=10, pad=5)
+            axes[i].axis('off')
+        except Exception as e:
+            # Handle error case
+            img_name = Path(img_path).name if hasattr(img_path, 'name') else str(img_path)
+            axes[i].text(0.5, 0.5, f"Error loading\n{img_name}",
+                        ha='center', va='center', transform=axes[i].transAxes)
+            axes[i].set_title(f"Slide {i+1} (Error)", fontsize=10, pad=5)
+            axes[i].axis('off')
+
+    # Hide any unused subplots
+    for i in range(num_images, len(axes)):
+        axes[i].axis('off')
+
+    plt.tight_layout()
+    plt.show()
+
+
+def display_slide_preview(
+    image_files: List[Union[str, Path]],
+    num_slides: int = 6,
+    max_cols: int = 3,
+    figsize_per_image: Tuple[int, int] = (4, 3)
+) -> None:
+    """
+    Display a preview of the first N slide images.
+
+    Args:
+        image_files: List of image file paths
+        num_slides: Number of slides to display (default: 6)
+        max_cols: Maximum number of columns in the grid (default: 3)
+        figsize_per_image: Size of each image subplot as (width, height) (default: (4, 3))
+
+    Example:
+        # Show first 6 slides
+        display_slide_preview(image_files, num_slides=6)
+
+        # Show first 8 slides in 4 columns
+        display_slide_preview(image_files, num_slides=8, max_cols=4)
+    """
+    total_slides = len(image_files)
+    slides_to_show = min(num_slides, total_slides)
+
+    print(f"\nDisplaying first {slides_to_show} of {total_slides} slide images:")
+    display_slide_grid(
+        image_files[:slides_to_show],
+        max_cols=max_cols,
+        figsize_per_image=figsize_per_image
+    )

end-to-end-use-cases/powerpoint-to-voiceover-transcript/uv.lock

@@ -1,5 +1,5 @@
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