Load Inverted Grayscale Image with PIL
Loads an image using PIL, converts it to grayscale, inverts pixel values so white is 0 and black is 255, and outputs a uint8 NumPy array.
npx skills add ECNU-ICALK/AutoSkill --skill load-inverted-grayscale-image-with-pil --agent claude-code
Same command for any agent — swap --agent for codex, cursor, copilot.
Weekly change comes from our own snapshots, not the repository page — it measures attention, not adoption.
# Load Inverted Grayscale Image with PIL Loads an image using PIL, converts it to grayscale, inverts pixel values so white is 0 and black is 255, and outputs a uint8 NumPy array. ## Prompt # Role & Objective You are a Python coding assistant specialized in image processing. Your task is to load an image file and convert it into a specific inverted grayscale NumPy array format. # Operational Rules & Constraints 1. Use the PIL (Pillow) library (`from PIL import Image`) to open the image file. 2. Convert the image to grayscale using the `convert('L')` method. 3. Convert the grayscale image object to a NumPy array with data type `uint8`. 4. Invert the pixel values of the array so that white pixels are represented as 0 and black pixels as 255. This is achieved by calculating `255 - array`. 5. If visualization is requested, use matplotlib with `cmap='gray'` to display the inverted image correctly. # Communication & Style Preferences Provide clear Python code snippets implementing the above logic. Ensure the code uses the specified libraries (PIL, numpy, matplotlib). ## Triggers - load image inverted grayscale - white pixel zero black 255 - pil image to inverted numpy array - convert imag
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What does the Load Inverted Grayscale Image with PIL skill do?
Loads an image using PIL, converts it to grayscale, inverts pixel values so white is 0 and black is 255, and outputs a uint8 NumPy array.
How do I install it?
Run `npx skills add ECNU-ICALK/AutoSkill --skill load-inverted-grayscale-image-with-pil --agent claude-code` — it drops the skill into your project so the agent can pick it up. Swap the --agent value for codex, cursor or copilot if you use one of those.
Where does this skill come from?
From ECNU-ICALK/AutoSkill, a repository with 539 stars. We read it straight from the repository tree rather than a submitted listing, so what you see here is what is actually published.
Is a popular skill a good skill?
Not necessarily. Stars measure attention, not adoption — a repository can trend for a week and be abandoned. That is why we show the weekly change from our own snapshots next to the total, instead of a single flattering number.