Merge branch 'main' into feature/add_flux1dev
This commit is contained in:
Fabio
commit
76f5f01d4c
52
README.md
52
README.md
@ -37,12 +37,29 @@ like [Numpy](https://numpy.org) and [Pillow](https://pypi.org/project/pillow/) f
|
||||
```
|
||||
### Generating an image
|
||||
|
||||
Run the provided [main.py](main.py)
|
||||
Run the provided [main.py](main.py) by specifying a prompt and some optional arguments like so:
|
||||
|
||||
```
|
||||
python main.py
|
||||
python main.py --prompt "Luxury food photograph" --steps 2 --seed 2
|
||||
```
|
||||
|
||||
or make a new separate script like the following
|
||||
#### Full list of Command-Line Arguments
|
||||
|
||||
- **`--prompt`** (required, `str`): Text description of the image to generate.
|
||||
|
||||
- **`--output`** (optional, `str`, default: `"image.png"`): Output image filename.
|
||||
|
||||
- **`--model`** (optional, `str`, default: `"black-forest-labs/FLUX.1-schnell"`): Model to use for generation.
|
||||
|
||||
- **`--seed`** (optional, `int`, default: `0`): Seed for random number generation. Default is time-based.
|
||||
|
||||
- **`--height`** (optional, `int`, default: `1024`): Height of the output image in pixels.
|
||||
|
||||
- **`--width`** (optional, `int`, default: `1024`): Width of the output image in pixels.
|
||||
|
||||
- **`--steps`** (optional, `int`, default: `4`): Number of inference steps.
|
||||
|
||||
Or make a new separate script like the following
|
||||
|
||||
```python
|
||||
import sys
|
||||
@ -60,6 +77,8 @@ image = flux.generate_image(
|
||||
prompt="Luxury food photograph of a birthday cake. In the middle it has three candles shaped like letters spelling the word 'MLX'. It has perfect lighting and a cozy background with big bokeh and shallow depth of field. The mood is a sunset balcony in tuscany. The photo is taken from the side of the cake. The scene is complemented by a warm, inviting light that highlights the textures and colors of the ingredients, giving it an appetizing and elegant look.",
|
||||
config=Config(
|
||||
num_inference_steps=2,
|
||||
height=768,
|
||||
width=1360,
|
||||
)
|
||||
)
|
||||
|
||||
@ -68,12 +87,28 @@ ImageUtil.save_image(image, "image.png")
|
||||
|
||||
If the model is not already downloaded on your machine, it will start the download process and fetch the model weights (~34GB in size for the Schnell model).
|
||||
|
||||
Generating a single image (with 2 inference steps, Schnell model) takes between 2 and 3 minutes. This implementation has been tested on two Macbook Pro machines:
|
||||
- 2021 M1 Pro (32 GB)
|
||||
- 2023 M2 Max (32 GB)
|
||||
|
||||
Update:
|
||||
On faster machines, [@karpathy](https://gist.github.com/awni/a67d16d50f0f492d94a10418e0592bde?permalink_comment_id=5153531#gistcomment-5153531) and [@awni](https://x.com/awnihannun/status/1823515121827897385) have reported times ~20s and below!
|
||||
### Image generation speed (updated)
|
||||
|
||||
These numbers are based on the Schnell model, with the configuration provided in the code snippet below.
|
||||
To time your machine, run the following:
|
||||
```
|
||||
time python main.py \
|
||||
--prompt "Luxury food photograph" \
|
||||
--steps 2 \
|
||||
--seed 2 \
|
||||
--height 1024 \
|
||||
--width 1024
|
||||
```
|
||||
|
||||
| Device | User | Reported Time |
|
||||
|--------------------|----------------------------------------------------------------------------------------------------------------------------|---------------|
|
||||
| M3 Max | [@karpathy](https://gist.github.com/awni/a67d16d50f0f492d94a10418e0592bde?permalink_comment_id=5153531#gistcomment-5153531) | ~20s |
|
||||
| M2 Ultra | [@awni](https://x.com/awnihannun/status/1823515121827897385) | <15s |
|
||||
| 2023 M2 Max (96GB) | [@explorigin](https://github.com/filipstrand/mflux/issues/6) | ~25s |
|
||||
| 2021 M1 Pro (16GB) | [@qw-in](https://github.com/filipstrand/mflux/issues/7) | ~175s |
|
||||
| 2021 M1 Pro (32GB) | @filipstrand | ~160s |
|
||||
| 2023 M2 Max (32GB) | @filipstrand | ~70s |
|
||||
|
||||
### Equivalent to Diffusers implementation
|
||||
|
||||
@ -134,4 +169,3 @@ Luxury food photograph of an italian Linguine pasta alle vongole dish with lots
|
||||
### TODO
|
||||
|
||||
- LoRA adapters
|
||||
- Command line args
|
||||
44
main.py
44
main.py
@ -1,5 +1,7 @@
|
||||
import os
|
||||
import sys
|
||||
import argparse
|
||||
import time
|
||||
|
||||
sys.path.append(os.path.abspath(os.path.join(os.path.dirname(__file__), 'src')))
|
||||
|
||||
@ -7,19 +9,37 @@ from flux_1_schnell.config.config import Config
|
||||
from flux_1_schnell.flux import Flux1
|
||||
from flux_1_schnell.post_processing.image_util import ImageUtil
|
||||
|
||||
flux = Flux1("black-forest-labs/FLUX.1-schnell", max_sequence_length=256)
|
||||
# flux = Flux1("black-forest-labs/FLUX.1-dev", max_sequence_length=512)
|
||||
def main():
|
||||
parser = argparse.ArgumentParser(description='Generate an image based on a prompt.')
|
||||
parser.add_argument('--prompt', type=str, required=True, help='The textual description of the image to generate.')
|
||||
parser.add_argument('--output', type=str, default="image.png", help='The filename for the output image. Default is "image.png".')
|
||||
parser.add_argument('--model', type=str, default="black-forest-labs/FLUX.1-schnell", help='The model to use. Default is "black-forest-labs/FLUX.1-schnell".')
|
||||
parser.add_argument('--max_sequence_length', type=int, default=256, help='Max Sequence Length (Default is 256)')
|
||||
parser.add_argument('--seed', type=int, default=0, help='Entropy Seed (Default is time-based random-seed)')
|
||||
parser.add_argument('--height', type=int, default=1024, help='Image height (Default is 1024)')
|
||||
parser.add_argument('--width', type=int, default=1024, help='Image width (Default is 1024)')
|
||||
parser.add_argument('--steps', type=int, default=4, help='Inference Steps')
|
||||
parser.add_argument('--guidance', type=float, default=3.5, help='Guidance Scale (Default is 3.5)')
|
||||
|
||||
args = parser.parse_args()
|
||||
|
||||
image = flux.generate_image(
|
||||
seed=3,
|
||||
prompt="Luxury food photograph of a birthday cake. In the middle it has three candles shaped like letters spelling the word 'MLX'. It has perfect lighting and a cozy background with big bokeh and shallow depth of field. The mood is a sunset balcony in tuscany. The photo is taken from the side of the cake. The scene is complemented by a warm, inviting light that highlights the textures and colors of the ingredients, giving it an appetizing and elegant look.",
|
||||
config=Config(
|
||||
num_inference_steps=2,
|
||||
height=768,
|
||||
width=1360,
|
||||
guidance=3.5,
|
||||
seed = args.seed or int(time.time())
|
||||
|
||||
flux = Flux1("black-forest-labs/FLUX.1-schnell", max_sequence_length=args.max_sequence_length)
|
||||
|
||||
image = flux.generate_image(
|
||||
seed=args.seed,
|
||||
prompt=args.prompt,
|
||||
config=Config(
|
||||
num_inference_steps=args.steps,
|
||||
height=args.height,
|
||||
width=args.width,
|
||||
guidance=args.guidance,
|
||||
)
|
||||
)
|
||||
)
|
||||
|
||||
ImageUtil.save_image(image, "image.png")
|
||||
ImageUtil.save_image(image, "image.png")
|
||||
|
||||
|
||||
if __name__ == '__main__':
|
||||
main()
|
||||
|
||||
Loading…
Reference in New Issue
Block a user