Metadata
- name
- image2pptx
- description
- Convert static images (slides, posters, infographics) to editable PowerPoint files. OCR detects text, classical CV textmask detects ink pixels, mask-clip preserves illustrations, LAMA inpaints clean background, python-pptx assembles editable text boxes with auto-scaled fonts and detected colors. Trigger on 'convert image to pptx', 'make slide editable', 'image to powerpoint', 'extract text from slide as editable', 'reconstruct slide', or when the user has a slide/poster image and wants an editable .pptx file.
- metadata
- {"author":"Jade Liu","source":"https://github.com/JadeLiu-tech/px-image2pptx"}
- risk
- low
image2pptx: Image to Editable PowerPoint
What It Does
Converts a static image into an editable .pptx file where every text element is a selectable, editable text box over a clean inpainted background.
- OCR (PaddleOCR PP-OCRv5) — detects text regions with bounding boxes and content
- Textmask (classical CV) — finds text ink pixels via adaptive thresholding
- Mask-clip — ANDs textmask with OCR bboxes to preserve non-text elements
- Inpaint (LAMA) — reconstructs masked regions with neural inpainting
- Assemble — places editable text boxes with auto-scaled fonts and detected colors
When to Use
| Scenario |
Recommendation |
| Slide with text on solid/flat background |
Best results |
| Slide with photo background |
Good — uses inpainting (warn about overlap areas) |
| Slide with solid background |
Good — use --skip-inpaint for speed |
| Chinese/multilingual slide |
Good — ch OCR handles both Chinese and English |
| Poster or infographic with text |
Good — works well if text is separate from graphics |
| Dense chart with axis labels on bars |
Caution — line grouping may over-merge crowded labels |
| Very thick/large decorative fonts |
Caution — may exceed standard mask dilation range |
| Extract individual assets as PNGs |
No — use px-asset-extract |
| Read text without creating PPTX |
No — use OCR directly |
| Edit an existing .pptx file |
No — use the pptx skill |
Installation
git clone https://github.com/JadeLiu-tech/px-image2pptx.git
cd px-image2pptx
pip install -e ".[all]"
Usage
CLI
px-image2pptx slide.png -o output.pptx
px-image2pptx slide.png -o output.pptx --lang ch
px-image2pptx slide.png -o output.pptx --skip-inpaint
px-image2pptx slide.png -o output.pptx --ocr-json text_regions.json
px-image2pptx slide.png -o output.pptx --work-dir ./debug/
Python API
from px_image2pptx import image_to_pptx
report = image_to_pptx("slide.png", "output.pptx")
# With options
report = image_to_pptx(
"slide.png", "output.pptx",
lang="ch",
skip_inpaint=False,
work_dir="./debug/",
)
CLI Options
| Option |
Default |
Description |
-o, --output |
output.pptx |
Output PPTX path |
--ocr-json |
|
Pre-computed OCR JSON (skips OCR) |
--lang |
auto |
OCR language: auto, en, ch |
--sensitivity |
16 |
Textmask sensitivity (lower = more) |
--dilation |
12 |
Textmask dilation pixels |
--min-font |
8 |
Min font size in points |
--max-font |
72 |
Max font size in points |
--skip-inpaint |
|
Skip LAMA inpainting |
--work-dir |
|
Save intermediate files |
Models
Downloaded automatically on first use (~370 MB total). All models are from official open-source repositories.
Models are cached locally after first download (~/.paddlex/official_models/ for OCR, ~/.cache/torch/hub/checkpoints/ for LAMA). To skip model downloads entirely, use --ocr-json with pre-computed OCR and --skip-inpaint.
Limitations — When to Warn the User
| Input |
Impact |
What to tell the user |
| Text on solid/flat background |
Best results |
No caveats needed |
| Text on textured background |
Good results |
LAMA handles repeating textures well |
| Text overlapping photos |
Inpainting artifacts likely |
"Areas where text covers photos may show blurring" |
| Dense chart with many labels |
Over-merged labels |
"Crowded labels may be grouped incorrectly" |
| Very thick/large fonts |
Incomplete mask coverage |
"Large fonts may exceed dilation range — try increasing --dilation" |
| Light text on dark background |
Blockier inpainting |
"White-on-dark text uses box masks instead of tight ink masks" |
| WebP image |
OCR fails (0 regions) |
Convert to PNG first: Image.open("in.webp").save("in.png") |
| Very large image (>4000px) |
Slow inpainting |
Suggest --skip-inpaint or downscaling |
| Decorative/handwritten fonts |
Typeface won't match |
"Fonts are reconstructed as Arial/Helvetica" |
| Centered/justified text |
Left-aligned output |
"Text alignment is not preserved" |
