jax-diffusers-event/canny_diffusiondb

1---2dataset_info:3  features:4  - name: original_image5    dtype: image6  - name: prompt7    dtype: string8  - name: transformed_image9    dtype: image10  splits:11  - name: train12    num_bytes: 604990210.013    num_examples: 99414  download_size: 60484970715  dataset_size: 604990210.016---17# Canny DiffusionDB 18 19This dataset is the [DiffusionDB dataset](https://huggingface.co/datasets/poloclub/diffusiondb) that is transformed using Canny transformation.20 21You can see samples below 👇 22 23**Sample:**24 25Original Image:26![image](https://datasets-server.huggingface.co/assets/merve/canny_diffusiondb/--/merve--canny_diffusiondb/train/0/original_image/image.jpg)27Transformed Image:28![image](https://datasets-server.huggingface.co/assets/merve/canny_diffusiondb/--/merve--canny_diffusiondb/train/0/transformed_image/image.jpg)29Caption:	30"a small wheat field beside a forest, studio lighting, golden ratio, details, masterpiece, fine art, intricate, decadent, ornate, highly detailed, digital painting, octane render, ray tracing reflections, 8 k, featured, by claude monet and vincent van gogh "31 32Below you can find a small script used to create this dataset:33```python34 35def canny_convert(image):36  image_array = np.array(image)37  gray_image = cv2.cvtColor(image_array, cv2.COLOR_BGR2GRAY)38  edges = cv2.Canny(gray_image, 100, 200)39  edge_image = Image.fromarray(edges)40  return edge_image41 42dataset = load_dataset("poloclub/diffusiondb", split = "train")43 44dataset_list = []45for data in dataset:46 47  image_path = data["image"]48  prompt = data["prompt"]49  transformed_image_path = canny_convert(image_path)50 51  new_data = {52      "original_image": image,53      "prompt": prompt,54      "transformed_image": transformed_image,55  }56  dataset_list.append(new_data)57 58```