Awesome
LAION-Aesthetics_Predictor V1
A linear estimator on top of clip to predict the aesthetic quality of pictures
Normal results:
<img src="cat_normal.png" width="512" />Aesthetic results:
<img src="cat_aesthetic.png" width="512" />visualization over laion2B http://3080.rom1504.fr/aesthetic/aesthetic_viz.html
integrated into https://rom1504.github.io/clip-retrieval/
import os
import torch
import torch.nn as nn
from os.path import expanduser # pylint: disable=import-outside-toplevel
from urllib.request import urlretrieve # pylint: disable=import-outside-toplevel
def get_aesthetic_model(clip_model="vit_l_14"):
"""load the aethetic model"""
home = expanduser("~")
cache_folder = home + "/.cache/emb_reader"
path_to_model = cache_folder + "/sa_0_4_"+clip_model+"_linear.pth"
if not os.path.exists(path_to_model):
os.makedirs(cache_folder, exist_ok=True)
url_model = (
"https://github.com/LAION-AI/aesthetic-predictor/blob/main/sa_0_4_"+clip_model+"_linear.pth?raw=true"
)
urlretrieve(url_model, path_to_model)
if clip_model == "vit_l_14":
m = nn.Linear(768, 1)
elif clip_model == "vit_b_32":
m = nn.Linear(512, 1)
else:
raise ValueError()
s = torch.load(path_to_model)
m.load_state_dict(s)
m.eval()
return m
That model takes clip embeddings as input
https://github.com/rom1504/embedding-reader/blob/main/examples/aesthetic_inference.py https://github.com/rom1504/embedding-reader/blob/main/examples/aesthetic_inference_emb.py