HED Boundary We use HED boundary detection [62] to obtain 3M edge-image-caption pairs
from internet. The model is trained with 300 GPU-hours with Nvidia A100 80G. The base model is
Stable Diffusion 1.5. (See also Fig. 7.)

User Sketching We synthesize human scribbles from images using a combination of HED boundary
detection [62] and a set of strong data augmentations (random thresholds, randomly masking out a
random percentage of scribbles, random morphological transformations, and random non-maximum
suppression). We obtain 500k scribble-image-caption pairs from internet. We use the above Canny
model as a starting checkpoint and train the model with 150 GPU-hours with Nvidia A100 80G. Note
that we also tried a more “human-like” synthesizing method [57] but the method is much slower than
a simple HED and we do not notice visible improvements. (See also Fig. 6.)
Adding Conditional Control to Text-to-Image Diffusion Models