chrissewell/TeamsLogoAdder
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# Ignore contents of input, logo, and output folders but keep the folders
input/*
logo/*
output/*
# Keep the folder structure by not ignoring .gitkeep files
!input/.gitkeep
!logo/.gitkeep
!output/.gitkeep
# Python
__pycache__/
*.py[cod]
*$py.class
*.so
.Python
build/
develop-eggs/
dist/
downloads/
eggs/
.eggs/
lib/
lib64/
parts/
sdist/
var/
wheels/
*.egg-info/
.installed.cfg
*.egg
MANIFEST
# IDEs
.vscode/
.idea/
*.swp
*.swo
*~
# OS
.DS_Store
.DS_Store?
._*
.Spotlight-V100
.Trashes
ehthumbs.db
Thumbs.db
# Temporary files
*.tmp
*.temp

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# TeamsFlipper - Image Processing Tool
TeamsFlipper is a Python script that processes images for video conferencing backgrounds by cropping, resizing, and adding logo overlays.
## Features
- **Batch Processing**: Automatically processes all `.jpg` and `.png` files in the input folder
- **Smart Cropping**: Crops images to 16:9 aspect ratio while preserving the center content
- **Standard Sizing**: Resizes all images to 2560x1440 pixels for consistent output
- **Logo Overlay**: Adds PNG logo from the logo directory to the upper-right corner
- **High Quality Output**: Saves processed images as high-quality JPEGs
## Installation
1. Clone this repository or download the files
2. Install required dependencies:
```bash
pip install -r requirements.txt
```
## Project Structure
```
TeamsFlipper/
├── flip_image.py # Main processing script
├── input/ # Place your source images here
├── logo/ # Place your logo PNG file here
│ └── cornerlogo.png # Example logo file
├── output/ # Processed images appear here
├── README.md # This file
├── requirements.txt # Python dependencies
└── .gitignore # Git ignore rules
```
## Usage
1. **Prepare your files:**
- Place your source images (`.jpg` or `.png`) in the `input/` folder
- Ensure your logo PNG file is in the `logo/` folder
2. **Run the script:**
```bash
python3 flip_image.py
```
3. **Get your results:**
- Processed images will be saved in the `output/` folder
- Output files are named `{original_filename}_logo.jpg`
## Processing Pipeline
The script performs the following operations on each image:
1. **Crop to 16:9**: Centers and crops the image to 16:9 aspect ratio
2. **Resize**: Scales the image to exactly 2560x1440 pixels
3. **Logo Overlay**: Places the logo (480px tall) in the exact upper-right corner
4. **Save**: Outputs as high-quality JPEG (95% quality)
## Logo Requirements
- **Format**: PNG with transparency support
- **Sizing**: Logo will be automatically resized to 480 pixels tall while maintaining aspect ratio
- **Position**: Logo is placed in the exact upper-right corner with no padding
## Supported Input Formats
- JPEG (`.jpg`, `.jpeg`)
- PNG (`.png`)
- Case-insensitive file extensions
## Output Format
- All processed images are saved as JPEG files
- Quality: 95% (high quality)
- Naming: `{original_filename}_logo.jpg`
- Size: 2560x1440 pixels (16:9 aspect ratio)
## Examples
### Input
- `my_photo.jpg` (any size/aspect ratio)
- Logo: `logo/company_logo.png`
### Output
- `output/my_photo_logo.jpg` (2560x1440 with logo overlay)
## Requirements
- Python 3.6+
- Pillow (PIL) library for image processing
## Troubleshooting
### No images found
- Ensure images are placed in the `input/` folder
- Check that file extensions are `.jpg`, `.jpeg`, or `.png`
### Logo not appearing
- Verify logo file exists in the `logo/` folder
- Ensure logo is in PNG format
- Check that logo file is not corrupted
### Processing errors
- Ensure input images are valid image files
- Check that you have write permissions for the `output/` folder
## License
This project is open source and available under standard terms.

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import os
import glob
from PIL import Image, ImageDraw
def crop_to_16_9(image):
"""Crop image to 16:9 aspect ratio, centering the crop."""
width, height = image.size
target_ratio = 16 / 9
current_ratio = width / height
if current_ratio > target_ratio:
# Image is too wide, crop width
new_width = int(height * target_ratio)
left = (width - new_width) // 2
right = left + new_width
cropped = image.crop((left, 0, right, height))
else:
# Image is too tall, crop height
new_height = int(width / target_ratio)
top = (height - new_height) // 2
bottom = top + new_height
cropped = image.crop((0, top, width, bottom))
return cropped
def resize_to_target(image, target_width=2560, target_height=1440):
"""Resize image to target dimensions."""
return image.resize((target_width, target_height), Image.Resampling.LANCZOS)
def overlay_logo(image, logo_path):
"""Overlay logo on the upper-right corner of the image."""
if not os.path.exists(logo_path):
print(f"Warning: Logo file {logo_path} not found. Skipping logo overlay.")
return image
try:
logo = Image.open(logo_path).convert("RGBA")
# Resize logo to be exactly 480 pixels tall while maintaining aspect ratio
logo_height = 480
logo_ratio = logo.size[0] / logo.size[1] # width / height
logo_width = int(logo_height * logo_ratio)
logo = logo.resize((logo_width, logo_height), Image.Resampling.LANCZOS)
# Get image dimensions
img_width, img_height = image.size
# Position logo in exact upper-right corner with no padding
x = img_width - logo_width
y = 0
# Create a copy of the image to work with
result = image.copy().convert("RGBA")
# Paste logo with transparency
result.paste(logo, (x, y), logo)
# Convert back to RGB
return result.convert("RGB")
except Exception as e:
print(f"Error overlaying logo: {e}")
return image
def process_images():
"""Process all .jpg and .png images in the input folder."""
input_folder = "input"
output_folder = "output"
logo_folder = "logo"
# Create output folder if it doesn't exist
os.makedirs(output_folder, exist_ok=True)
# Find logo file in logo directory
logo_files = glob.glob(os.path.join(logo_folder, "*.png"))
if not logo_files:
# Fallback to cornerlogo.png in root directory
if os.path.exists("cornerlogo.png"):
logo_path = "cornerlogo.png"
print("Using cornerlogo.png from root directory")
else:
logo_path = None
print("Warning: No logo file found")
else:
logo_path = logo_files[0] # Use first PNG found in logo directory
print(f"Using logo: {logo_path}")
# Find all image files in input folder
image_extensions = ["*.jpg", "*.jpeg", "*.png", "*.JPG", "*.JPEG", "*.PNG"]
image_files = []
for extension in image_extensions:
image_files.extend(glob.glob(os.path.join(input_folder, extension)))
if not image_files:
print(f"No image files found in {input_folder} folder.")
return
print(f"Found {len(image_files)} image(s) to process:")
for image_path in image_files:
try:
print(f"Processing: {os.path.basename(image_path)}")
# Open and process the image
with Image.open(image_path) as img:
# Convert to RGB if necessary
if img.mode != 'RGB':
img = img.convert('RGB')
# Step 1: Crop to 16:9 aspect ratio
cropped_img = crop_to_16_9(img)
# Step 2: Resize to 2560x1440
resized_img = resize_to_target(cropped_img)
# Step 3: Overlay logo
if logo_path:
logo_img = overlay_logo(resized_img, logo_path)
else:
logo_img = resized_img
# Step 4: Save as JPG in output folder
base_name = os.path.splitext(os.path.basename(image_path))[0]
output_path = os.path.join(output_folder, f"{base_name}_logo.jpg")
logo_img.save(output_path, "JPEG", quality=95)
print(f"Saved: {output_path}")
except Exception as e:
print(f"Error processing {image_path}: {e}")
def main():
"""Main function to process images."""
print("TeamsFlipper - Image Processing Tool")
print("=" * 40)
process_images()
print("Processing complete!")
if __name__ == '__main__':
main()

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Pillow>=9.0.0