From bc07ce62c179d3aab3053a623d96a071101d11cb Mon Sep 17 00:00:00 2001 From: pharmapsychotic Date: Sat, 9 Sep 2023 19:11:06 -0500 Subject: [PATCH] Update cog --- cog.yaml | 20 ++++++++------------ predict.py | 19 +++++++++++-------- 2 files changed, 19 insertions(+), 20 deletions(-) diff --git a/cog.yaml b/cog.yaml index 638f2c6..da14215 100644 --- a/cog.yaml +++ b/cog.yaml @@ -1,20 +1,16 @@ build: gpu: true - cuda: "11.6" - python_version: "3.8" + cuda: "11.8" + python_version: "3.10" system_packages: - "libgl1-mesa-glx" - "libglib2.0-0" python_packages: - - "ipython==8.4.0" - - "fairscale==0.4.12" - - "transformers==4.21.2" - - "ftfy==6.1.1" - - "torch==1.13.0 --extra-index-url=https://download.pytorch.org/whl/cu116" - - "torchvision==0.14.0 --extra-index-url=https://download.pytorch.org/whl/cu116" - - "open_clip_torch==2.7.0" - - "timm==0.4.12" - - "pycocoevalcap==1.2" - - "git+https://github.com/pharmapsychotic/BLIP.git" + - "Pillow==10.0.0" + - "safetensors==0.3.3" + - "tqdm==4.66.1" + - "open_clip_torch==2.20.0" + - "accelerate==0.22.0" + - "transformers==4.33.1" predict: "predict.py:Predictor" diff --git a/predict.py b/predict.py index abceb28..19625f1 100644 --- a/predict.py +++ b/predict.py @@ -2,13 +2,12 @@ import sys from PIL import Image from cog import BasePredictor, Input, Path -from clip_interrogator import Interrogator, Config +from clip_interrogator import Config, Interrogator class Predictor(BasePredictor): def setup(self): self.ci = Interrogator(Config( - blip_model_url='cache/model_large_caption.pth', clip_model_name="ViT-L-14/openai", clip_model_path='cache', device='cuda:0', @@ -19,23 +18,27 @@ class Predictor(BasePredictor): image: Path = Input(description="Input image"), clip_model_name: str = Input( default="ViT-L-14/openai", - choices=["ViT-L-14/openai", "ViT-H-14/laion2b_s32b_b79k"], - description="Choose ViT-L for Stable Diffusion 1, and ViT-H for Stable Diffusion 2", + choices=["ViT-L-14/openai", "ViT-H-14/laion2b_s32b_b79k", "ViT-bigG-14/laion2b_s39b_b160k"], + description="Choose ViT-L for Stable Diffusion 1, ViT-H for Stable Diffusion 2, or ViT-bigG for Stable Diffusion XL.", ), mode: str = Input( default="best", - choices=["best", "fast"], + choices=["best", "classic", "fast", "negative"], description="Prompt mode (best takes 10-20 seconds, fast takes 1-2 seconds).", ), ) -> str: """Run a single prediction on the model""" image = Image.open(str(image)).convert("RGB") self.switch_model(clip_model_name) - if mode == "best": + if mode == 'best': return self.ci.interrogate(image) - else: + elif mode == 'classic': + return self.ci.interrogate_classic(image) + elif mode == 'fast': return self.ci.interrogate_fast(image) - + elif mode == 'negative': + return self.ci.interrogate_negative(image) + def switch_model(self, clip_model_name: str): if clip_model_name != self.ci.config.clip_model_name: self.ci.config.clip_model_name = clip_model_name