disclaimer: more than half of this was generated using Claude Code to give me something to modify and play with.
A collection of scripts and Python tools for processing card images - detecting rectangles, cropping, rotating, and trimming whitespace from large card images.
These have been used with tampermonkey, should work with others.
When viewing checklists, this adds a new "Add Card" button that will open the add card page in an iframe in the same window and trim some things off to make it quicker to add cards from the same set.
On the add card page, this will collapse the Grading options into a toggleable area (defaults to closed) as well as saving the cost and purchase date when you save. Those values will then be prepopulated for the next hour to facilitate adding cards quicker.
When clicking the (new green) "Open Missing Image List" button while viewing a category of your collection, the page will scroll to the end (be patient) and collect a list of every card that is displaying the "no image" placeholder and open the list in a new tab so you can go find them.
While viewing a category of your collection, hover over the (new green) "Show Missing Images" button - there are two options, both of which modify the list so only ones displaying the "no image" placeholder are shown.
-
Visible - this will remove the "load more" functionality and filter out cards from what's currently loaded/visible. By default when the page loads, that's 50 cards max. This can be useful after adding cards and quicker then going through everything. The page must currently be reloaded to undo this.
-
All - like with "Show User List", this scrolls throught the entire category, then applies the "Visible" filtering above, effectively filtering the entire category.
Currently does two things:
- Keeps a list of the last 5 useful on-site pages visited and displaus it along with a link to your collection in the upper right.
- Applies custom styles
You'll probably want to minify these before saving them as bookmarklets.
javascript: (function () {
document.querySelectorAll("tr.offer").forEach(function (row) {
row.style.display = "none";
});
document.querySelectorAll("tr.offer").forEach(function (row) {
if (
row.querySelector(
'img[src="https://www.pricecharting.com/images/no-image-available.png"]'
)
) {
row.style.display = "";
} else {
var nextRow = row.nextElementSibling;
if (nextRow && nextRow.classList.contains("gap")) {
nextRow.style.display = "none";
}
}
});
})();javascript: (function () {
let t = [],
r = document.querySelectorAll("tr.offer");
r.forEach((e) => {
if (
e.querySelector(
'img[src="https://www.pricecharting.com/images/no-image-available.png"]'
)
) {
let n = e.querySelector("p.title");
if (n) {
let i = n.innerHTML
.replace(/<br\/?>/gi, " - ")
.replace(/<[^>]*>/g, "")
.trim()
.replace(/\s+/g, " ")
.trim()
.split(" - ");
if (i.length === 2) {
i = i[1] + " - " + i[0];
}
t.push(i);
}
}
});
if (t.length > 0) {
t = t.sort();
let e = window.open("", "_blank");
e.document.write(
"<title>" +
t.length +
' cards missing images</title><textarea style="width:90%;height:90%;">' +
t.join("\n") +
"</textarea>"
);
e.document.querySelector("textarea").select();
} else {
alert("No matching rows found.");
}
})();- Python 3.6+
- OpenCV (
opencv-python) - NumPy
- ImageMagick (for whitespace trimming)
# For a regular installation
pip install .
# or to install in development mode
pip install -e .The main combined tool that handles the full workflow:
- Detecting rectangles in images
- Cropping and rotating them
- Trimming whitespace from the cropped images
process-cards image1.jpg image2.pngUninstalled command:
python process_cards.py <args>input_files: One or more input image files (supports glob patterns like*.jpg)-n, --max_rectangles: Maximum number of rectangles to crop per image (default: 20)-a, --min_area: Minimum area of rectangles to consider (default: 500000 for large cards)-c, --contours: Save visualization of detected contours
# Process all JPG files in a directory
process-cards "images/*.jpg"
# Process with contour visualization
process-cards image.jpg -c
# Process with custom settings
process-cards image.jpg -n 10 -a 500000All processed images are saved in a timestamped directory:
processed/
└── YYYY-MM-DD_HH-MM-SS/
├── original_image-cropped-1.png
├── original_image-cropped-2.png
├── original_image-contours-raw.png (if -c option used)
├── original_image-contours-filtered.png (if -c option used)
├── debug/ (if -c option used)
│ ├── original_image-gray.png
│ ├── original_image-blurred.png
│ ├── original_image-edges.png
│ ├── original_image-dilated_edges.png
│ ├── original_image-rotated-1.png
│ └── original_image-cropped-debug-1.png
└── trimmed/
├── original_image-cropped-1-trimmed.png
└── original_image-cropped-2-trimmed.png
python process_cards.py <args>Finds, crops, and rotates rectangular card images.
find-recs path/to/image.jpgOptions:
-o,--output_dir: Output directory (default: "cropped_rectangles")-n,--max_rectangles: Maximum number of rectangles to crop (default: 20)-a,--min_area: Minimum area of rectangles to consider (default: 1000 in the original script, 500000 recommended for large cards)
python find_recs.py <args>Trims whitespace from images using ImageMagick.
trim-whitespace path/to/image.jpgUninstalled command:
python trim_whitespace.py <args># Import individual functions
from find_recs import crop_and_rotate_rectangles
from trim_whitespace import trim_image
# Find and crop rectangles
crop_and_rotate_rectangles("image.jpg", output_dir="output", max_rectangles=5)
# Trim whitespace from an image
trim_image("image.jpg")
# Or use the combined process_cards functionality
from process_cards import process_image, create_output_directory
# Create a timestamped output directory
output_dir = create_output_directory()
# Process an image (detect rectangles, crop, rotate, and trim whitespace)
process_image("image.jpg", output_dir, max_rectangles=5, min_area=500000, draw_contours=True)