Auto-install instruction: When you share this link with any AI agent, it will automatically fetch and install the NotebookLM Experts skill to the correct location on your system.
Compatible with: Claude Code · GitHub Copilot · OpenAI Codex CLI · Gemini CLI · and other agent frameworks
| import os | |
| from PIL import Image | |
| root_folder = "folder_path" | |
| def convert_ppm_to_jpg(folder_path): | |
| for root, dirs, files in os.walk(folder_path): | |
| for filename in files: | |
| if filename.endswith(".ppm"): |
| import os | |
| from PIL import Image | |
| root_folder = "folder_path" | |
| def convert_image_to_ppm(folder_path): | |
| for root, dirs, files in os.walk(folder_path): | |
| for filename in files: | |
| if filename.endswith((".png", ".jpg")): |
| #include <stdio.h> | |
| #include <time.h> | |
| typedef struct { | |
| double Kp; | |
| double Ki; | |
| double Kd; | |
| double sample_time; | |
| double current_time; | |
| double last_time; |
| import json | |
| import os | |
| from PIL import Image, ImageDraw | |
| ############################################## | |
| # - image_label: | |
| # - 1.json | |
| # - 1.jpg | |
| # - 2.json | |
| # - 2.jpg |
| import keras | |
| from keras.datasets import mnist | |
| from keras.models import Sequential | |
| from keras.layers import Dense, Activation, Flatten, Input | |
| from keras.layers import Conv2D, MaxPooling2D, UpSampling2D | |
| import matplotlib.pyplot as plt | |
| from keras import backend as K | |
| import numpy as np | |
| from keras.preprocessing.image import ImageDataGenerator, array_to_img, img_to_array, load_img |