jax-diffusers-event/canny_diffusiondb
Canny DiffusionDB This dataset is the DiffusionDB dataset that is transformed using Canny transformation. You can see samples below 👇 Sample: Original Image: Transformed Image: Caption: "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 " Below you can find a small script… See the full description on the dataset page: https://huggingface.co/datasets/jax-diffusers-event/canny_diffusiondb.
Canny DiffusionDB
This dataset is the DiffusionDB dataset that is transformed using Canny transformation.
You can see samples below 👇
Sample:
Original Image: 
Transformed Image: 
Caption: "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 "
Below you can find a small script used to create this dataset:
def canny_convert(image):
image_array = np.array(image)
gray_image = cv2.cvtColor(image_array, cv2.COLOR_BGR2GRAY)
edges = cv2.Canny(gray_image, 100, 200)
edge_image = Image.fromarray(edges)
return edge_image
dataset = load_dataset("poloclub/diffusiondb", split = "train")
dataset_list = []
for data in dataset:
image_path = data["image"]
prompt = data["prompt"]
transformed_image_path = canny_convert(image_path)
new_data = {
"original_image": image,
"prompt": prompt,
"transformed_image": transformed_image,
}
dataset_list.append(new_data)