Some code I used to experiment with Flux-schnell on an M2 macbook pro using MLX.
Allows two types of image generation: prompt driven generation and iterative image driven generation. As the name suggests, prompt driven generation simply generates an image from a given prompt. Iterative image driven generation on the other hand, iteratively generates an image based on a previously generated image.
Prompt driven generation example:
python generate.py prompt "A snow monkey sitting in a hotspring, photorealistic" monke.png --steps 100 --seed 123Iterative image driven generation example:
python generate.py image_loop "monke.png" "monke" 900 --steps 10 --denoise 0.23 --seed 123 --contHere, the script will iteratively generate 900 images in the directory 'monke'. --cont tells the script to continue from the last image in the directory 'monke', if this exists. The denoise value can be adjusted to increase and decrease how much a new image differs from it's predecessor.
This script converts the iteratively generated images from the image_loop mode into a video.
python createVideo.py monke 16 monke.mp4In the example above, a framerate of 16 has been chosen. Below an example is shown of how such a video can look.
