adetailer [Bug]: Segmentation models not working with newest ultralytics version

Describe the bug

Segmentation models do not apply inpainting anymore because newest ultralytics is not fully compatible with adetailer.

Bbox works fine.

I fixed this by making a fork and pinning the max ultralytics version to the same as the min version. ("8.3.75")

A proper fix for this would be highly appreciated!

Steps to reproduce

No response

Screenshots

No response

Console logs, from start to end.

List of installed extensions

No response

Oct 29 '25 02:10 Byt3Sh0ck

Hi @Byt3Sh0ck! I'm Dosu and I’m helping the adetailer team.

This is a known issue: segmentation models in adetailer break with newer ultralytics versions due to upstream API changes, while bbox models keep working. There are no recent fixes or workarounds in the codebase or documentation beyond pinning ultralytics to version 8.3.75, which matches your approach. The code expects segmentation masks in a format that changed in newer ultralytics releases, and there’s no version check or adaptation logic in adetailer, so breakage is likely with any update past 8.3.75. For now, pinning ultralytics to 8.3.75 is the only reliable solution until a proper compatibility update is made in adetailer itself. More details and related discussion can be found here.

To reply, just mention @dosu.

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Oct 29 '25 02:10 dosubot[bot]

현재 최신버전인 v8.3.221에서도 정상 동작함을 확인했습니다.

Oct 29 '25 08:10 Bing-su

현재 최신버전인 v8.3.221에서도 정상 동작함을 확인했습니다.

Thank you for the reply.

Hmm. There were multiple people in this reddit post that could not get it to work, including me: https://www.reddit.com/r/StableDiffusion/comments/1oc3410/i_reinstalled_forge_and_reforge_and_now/

The only solution for me was to pin ultralytics to 8.3.75. These versions did NOT work for us:

Does not work: Forge Classic: ultralytics 8.3.220 mediapipe 0.10.14 rich 13.9.2

Reforge: ultralytics 8.3.221 mediapipe 0.10.14 rich 14.2.0

Works: A1111: ultralytics 8.3.61 mediapipe 0.10.14 rich 13.7.1

Oct 29 '25 11:10 Byt3Sh0ck

I did some tests on my old Nvidia PC (GTX1080) and there Segmentation models work with: :white_check_mark:Auto1111 Ultralytics: 8.3.203 rich: 14.1.0 mediapipe: 0.10.14 :white_check_mark: Forge Ultralytics: 8.3.49 rich: 13.7.1 mediapipe: 0.10.14 :white_check_mark: ReForge Ultralytics: 8.3.203 rich: 14.1.0 mediapipe: 0.10.14

Worked not on: :x: Forge Classic Ultralytics: 8.3.221 rich: 13.9.4 mediapipe 0.10.14

:x: On my AMD PC with Forge Neo it does't worked either: Ultralytics: 8.3.220, 8.3.221, and the new 8.3.222 rich 14.2.0 mediapipe 0.10.14

Everything tested on Python 3.11.9

Downgrading to 8.3.203 worked on Forge classic and neo.

Solution: ⚠️I then tested every Version from 8.3.222 back down until it started to work. ➡️ The latest Version that works for me is: 8.3.216

So something in 8.3.217, that got released 2 weeks ago, broke the compatibility with adetailer.

Used these commands to downgrade (cmd needs to be opened inside the root webui folder): venv\Scripts\activate.bat pip uninstall ultralytics -y pip install ultralytics==8.3.216

Oct 29 '25 16:10 CS1o

I did some tests on my old Nvidia PC (GTX1080) and there Segmentation models work with: ✅Auto1111 Ultralytics: 8.3.203 rich: 14.1.0 mediapipe: 0.10.14 ✅ Forge Ultralytics: 8.3.49 rich: 13.7.1 mediapipe: 0.10.14 ✅ ReForge Ultralytics: 8.3.203 rich: 14.1.0 mediapipe: 0.10.14

Worked not on: ❌ Forge Classic Ultralytics: 8.3.221 rich: 13.9.4 mediapipe 0.10.14

❌ On my AMD PC with Forge Neo it does't worked either: Ultralytics: 8.3.220, 8.3.221, and the new 8.3.222 rich 14.2.0 mediapipe 0.10.14

Everything tested on Python 3.11.9

Downgrading to 8.3.203 worked on Forge classic and neo.

Solution: ⚠️I then tested every Version from 8.3.222 back down until it started to work. ➡️ The latest Version that works for me is: 8.3.216

So something in 8.3.217, that got released 2 weeks ago, broke the compatibility with adetailer.

Used these commands to downgrade (cmd needs to be opened inside the root webui folder): venv\Scripts\activate.bat pip uninstall ultralytics -y pip install ultralytics==8.3.216

Can confirm 8.3.216 works on forge classic.

Oct 29 '25 16:10 Byt3Sh0ck

I did some tests on my old Nvidia PC (GTX1080) and there Segmentation models work with: ✅Auto1111 Ultralytics: 8.3.203 rich: 14.1.0 mediapipe: 0.10.14 ✅ Forge Ultralytics: 8.3.49 rich: 13.7.1 mediapipe: 0.10.14 ✅ ReForge Ultralytics: 8.3.203 rich: 14.1.0 mediapipe: 0.10.14

Worked not on: ❌ Forge Classic Ultralytics: 8.3.221 rich: 13.9.4 mediapipe 0.10.14

❌ On my AMD PC with Forge Neo it does't worked either: Ultralytics: 8.3.220, 8.3.221, and the new 8.3.222 rich 14.2.0 mediapipe 0.10.14

Everything tested on Python 3.11.9

Downgrading to 8.3.203 worked on Forge classic and neo.

Solution: ⚠️I then tested every Version from 8.3.222 back down until it started to work. ➡️ The latest Version that works for me is: 8.3.216

So something in 8.3.217, that got released 2 weeks ago, broke the compatibility with adetailer.

Used these commands to downgrade (cmd needs to be opened inside the root webui folder): venv\Scripts\activate.bat pip uninstall ultralytics -y pip install ultralytics==8.3.216

Thank you.

I had the same problem with Forge Neo.

Your solution solved it.

Nov 03 '25 01:11 DDaDaDak

기본으로 내장된 faceyolov8n이나 다른 bbox 모델을 사용하면 잘 되는데 99coins_anime_girl_face_m_seg.pt 이나 Anzhc Face seg 640 v2 y8n.pt 처럼 얼굴 전체 사각형이 아니라 얼굴 부분만 인페인팅하는 seg 모델을 받아서 사용할 경우 안되네요 오류 메시지도 없고, 0.91 이런 점수 나오면서 얼굴부분이 파란색으로 인식되긴 하는데 정작 얼굴 수정은 안됨 A1111 ultralytics==8.3.222

Nov 21 '25 11:11 Ineman

i uninstall with cache deleted for ultralytics and install ultralytics==8.3.216 and y try with ==8.3.203 and not works:

[-] ADetailer: nothing detected on image 1 with 1st settings.

(venv) root@f9b4d6272646:/workspace/sd-webui-forge-neo# pip uninstall ultralytics -ytralytics -y pip install ultralytics==8.3.216 Found existing installation: ultralytics 8.3.203 Uninstalling ultralytics-8.3.203: Successfully uninstalled ultralytics-8.3.203 Collecting ultralytics==8.3.216 Downloading ultralytics-8.3.216-py3-none-any.whl.metadata (37 kB) Requirement already satisfied: numpy>=1.23.0 in ./venv/lib/python3.12/site-packages (from ultralytics==8.3.216) (1.26.4) Requirement already satisfied: matplotlib>=3.3.0 in ./venv/lib/python3.12/site-packages (from ultralytics==8.3.216) (3.10.7) Requirement already satisfied: opencv-python>=4.6.0 in ./venv/lib/python3.12/site-packages (from ultralytics==8.3.216) (4.8.1.78) Requirement already satisfied: pillow>=7.1.2 in ./venv/lib/python3.12/site-packages (from ultralytics==8.3.216) (10.4.0) Requirement already satisfied: pyyaml>=5.3.1 in ./venv/lib/python3.12/site-packages (from ultralytics==8.3.216) (6.0.3) Requirement already satisfied: requests>=2.23.0 in ./venv/lib/python3.12/site-packages (from ultralytics==8.3.216) (2.32.5) Requirement already satisfied: scipy>=1.4.1 in ./venv/lib/python3.12/site-packages (from ultralytics==8.3.216) (1.16.3) Requirement already satisfied: torch>=1.8.0 in ./venv/lib/python3.12/site-packages (from ultralytics==8.3.216) (2.8.0) Requirement already satisfied: torchvision>=0.9.0 in ./venv/lib/python3.12/site-packages (from ultralytics==8.3.216) (0.23.0) Requirement already satisfied: psutil in ./venv/lib/python3.12/site-packages (from ultralytics==8.3.216) (5.9.8) Requirement already satisfied: polars in ./venv/lib/python3.12/site-packages (from ultralytics==8.3.216) (1.35.2) Requirement already satisfied: ultralytics-thop>=2.0.0 in ./venv/lib/python3.12/site-packages (from ultralytics==8.3.216) (2.0.18) Requirement already satisfied: contourpy>=1.0.1 in ./venv/lib/python3.12/site-packages (from matplotlib>=3.3.0->ultralytics==8.3.216) (1.3.3) Requirement already satisfied: cycler>=0.10 in ./venv/lib/python3.12/site-packages (from matplotlib>=3.3.0->ultralytics==8.3.216) (0.12.1) Requirement already satisfied: fonttools>=4.22.0 in ./venv/lib/python3.12/site-packages (from matplotlib>=3.3.0->ultralytics==8.3.216) (4.60.1) Requirement already satisfied: kiwisolver>=1.3.1 in ./venv/lib/python3.12/site-packages (from matplotlib>=3.3.0->ultralytics==8.3.216) (1.4.9) Requirement already satisfied: packaging>=20.0 in ./venv/lib/python3.12/site-packages (from matplotlib>=3.3.0->ultralytics==8.3.216) (24.2) Requirement already satisfied: pyparsing>=3 in ./venv/lib/python3.12/site-packages (from matplotlib>=3.3.0->ultralytics==8.3.216) (3.2.5) Requirement already satisfied: python-dateutil>=2.7 in ./venv/lib/python3.12/site-packages (from matplotlib>=3.3.0->ultralytics==8.3.216) (2.9.0.post0) Requirement already satisfied: charset_normalizer<4,>=2 in ./venv/lib/python3.12/site-packages (from requests>=2.23.0->ultralytics==8.3.216) (3.4.4) Requirement already satisfied: idna<4,>=2.5 in ./venv/lib/python3.12/site-packages (from requests>=2.23.0->ultralytics==8.3.216) (3.11) Requirement already satisfied: urllib3<3,>=1.21.1 in ./venv/lib/python3.12/site-packages (from requests>=2.23.0->ultralytics==8.3.216) (2.5.0) Requirement already satisfied: certifi>=2017.4.17 in ./venv/lib/python3.12/site-packages (from requests>=2.23.0->ultralytics==8.3.216) (2025.10.5) Requirement already satisfied: filelock in ./venv/lib/python3.12/site-packages (from torch>=1.8.0->ultralytics==8.3.216) (3.20.0) Requirement already satisfied: typing-extensions>=4.10.0 in ./venv/lib/python3.12/site-packages (from torch>=1.8.0->ultralytics==8.3.216) (4.15.0) Requirement already satisfied: setuptools in ./venv/lib/python3.12/site-packages (from torch>=1.8.0->ultralytics==8.3.216) (69.5.1) Requirement already satisfied: sympy>=1.13.3 in ./venv/lib/python3.12/site-packages (from torch>=1.8.0->ultralytics==8.3.216) (1.14.0) Requirement already satisfied: networkx in ./venv/lib/python3.12/site-packages (from torch>=1.8.0->ultralytics==8.3.216) (3.5) Requirement already satisfied: jinja2 in ./venv/lib/python3.12/site-packages (from torch>=1.8.0->ultralytics==8.3.216) (3.1.6) Requirement already satisfied: fsspec in ./venv/lib/python3.12/site-packages (from torch>=1.8.0->ultralytics==8.3.216) (2025.10.0) Requirement already satisfied: nvidia-cuda-nvrtc-cu12==12.8.93 in ./venv/lib/python3.12/site-packages (from torch>=1.8.0->ultralytics==8.3.216) (12.8.93) Requirement already satisfied: nvidia-cuda-runtime-cu12==12.8.90 in ./venv/lib/python3.12/site-packages (from torch>=1.8.0->ultralytics==8.3.216) (12.8.90) Requirement already satisfied: nvidia-cuda-cupti-cu12==12.8.90 in ./venv/lib/python3.12/site-packages (from torch>=1.8.0->ultralytics==8.3.216) (12.8.90) Requirement already satisfied: nvidia-cudnn-cu12==9.10.2.21 in ./venv/lib/python3.12/site-packages (from torch>=1.8.0->ultralytics==8.3.216) (9.10.2.21) Requirement already satisfied: nvidia-cublas-cu12==12.8.4.1 in ./venv/lib/python3.12/site-packages (from torch>=1.8.0->ultralytics==8.3.216) (12.8.4.1) Requirement already satisfied: nvidia-cufft-cu12==11.3.3.83 in ./venv/lib/python3.12/site-packages (from torch>=1.8.0->ultralytics==8.3.216) (11.3.3.83) Requirement already satisfied: nvidia-curand-cu12==10.3.9.90 in ./venv/lib/python3.12/site-packages (from torch>=1.8.0->ultralytics==8.3.216) (10.3.9.90) Requirement already satisfied: nvidia-cusolver-cu12==11.7.3.90 in ./venv/lib/python3.12/site-packages (from torch>=1.8.0->ultralytics==8.3.216) (11.7.3.90) Requirement already satisfied: nvidia-cusparse-cu12==12.5.8.93 in ./venv/lib/python3.12/site-packages (from torch>=1.8.0->ultralytics==8.3.216) (12.5.8.93) Requirement already satisfied: nvidia-cusparselt-cu12==0.7.1 in ./venv/lib/python3.12/site-packages (from torch>=1.8.0->ultralytics==8.3.216) (0.7.1) Requirement already satisfied: nvidia-nccl-cu12==2.27.3 in ./venv/lib/python3.12/site-packages (from torch>=1.8.0->ultralytics==8.3.216) (2.27.3) Requirement already satisfied: nvidia-nvtx-cu12==12.8.90 in ./venv/lib/python3.12/site-packages (from torch>=1.8.0->ultralytics==8.3.216) (12.8.90) Requirement already satisfied: nvidia-nvjitlink-cu12==12.8.93 in ./venv/lib/python3.12/site-packages (from torch>=1.8.0->ultralytics==8.3.216) (12.8.93) Requirement already satisfied: nvidia-cufile-cu12==1.13.1.3 in ./venv/lib/python3.12/site-packages (from torch>=1.8.0->ultralytics==8.3.216) (1.13.1.3) Requirement already satisfied: triton==3.4.0 in ./venv/lib/python3.12/site-packages (from torch>=1.8.0->ultralytics==8.3.216) (3.4.0) Requirement already satisfied: polars-runtime-32==1.35.2 in ./venv/lib/python3.12/site-packages (from polars->ultralytics==8.3.216) (1.35.2) Requirement already satisfied: six>=1.5 in ./venv/lib/python3.12/site-packages (from python-dateutil>=2.7->matplotlib>=3.3.0->ultralytics==8.3.216) (1.17.0) Requirement already satisfied: mpmath<1.4,>=1.1.0 in ./venv/lib/python3.12/site-packages (from sympy>=1.13.3->torch>=1.8.0->ultralytics==8.3.216) (1.3.0) Requirement already satisfied: MarkupSafe>=2.0 in ./venv/lib/python3.12/site-packages (from jinja2->torch>=1.8.0->ultralytics==8.3.216) (2.1.5) Downloading ultralytics-8.3.216-py3-none-any.whl (1.1 MB) ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 1.1/1.1 MB 7.3 MB/s eta 0:00:00 Installing collected packages: ultralytics Successfully installed ultralytics-8.3.216 (venv) root@f9b4d6272646:/workspace/sd-webui-forge-neo# python webui.py --listen --port 9998 --api --disable-safe-unpickle --enable-insecure-extension-access --skip-prepare-environment --skip-python-version-check --skip-torch-cuda-test --skip-version-check --cuda-malloc --cuda-stream --pin-shared-memory --sage2-function fp16_triton Using cudaMallocAsync backend. Total VRAM 32110 MB, total RAM 192325 MB pytorch version: 2.8.0+cu128 Set vram state to: NORMAL_VRAM Always pin shared GPU memory Device: cuda:0 NVIDIA GeForce RTX 5090 : cudaMallocAsync VAE dtype preferences: [torch.bfloat16, torch.float32] -> torch.bfloat16 CUDA Using Stream: True Using SageAttention (fp16 Triton) Using PyTorch Attention for VAE ControlNet preprocessor location: /workspace/sd-webui-forge-neo/models/ControlNetPreprocessor [-] ADetailer initialized. version: 25.3.0, num models: 13 [ControlNet] - INFO - ControlNet UI callback registered. Model selected: {'checkpoint_info': {'filename': '/workspace/sd-webui-forge-neo/models/Stable-diffusion/checkpoints/flux1-dev.safetensors', 'hash': 'b04b3ba1'}, 'additional_modules': ['/workspace/sd-webui-forge-neo/models/VAE/ae.safetensors', '/workspace/sd-webui-forge-neo/models/text_encoder/clip_l.safetensors', '/workspace/sd-webui-forge-neo/models/text_encoder/t5xxl_fp16.safetensors'], 'unet_storage_dtype': None} Using online LoRAs in FP16: False Running on local URL: http://0.0.0.0:9998

To create a public link, set share=True in launch(). Startup time: 84.6s (forge init: 34.9s, import torch: 20.8s, initialize shared: 0.6s, other imports: 16.1s, setup gfpgan: 0.2s, list SD models: 2.9s, load scripts: 5.7s, create ui: 1.5s, gradio launch: 1.0s, add APIs: 0.6s). Environment vars changed: {'stream': False, 'inference_memory': 2038.4, 'pin_shared_memory': False} [GPU Setting] You will use 93.62% GPU memory (30061.00 MB) to load weights, and use 6.38% GPU memory (2048.00 MB) to do matrix computation. Loading Model: {'checkpoint_info': {'filename': '/workspace/sd-webui-forge-neo/models/Stable-diffusion/checkpoints/flux1-dev.safetensors', 'hash': 'b04b3ba1'}, 'additional_modules': ['/workspace/sd-webui-forge-neo/models/VAE/ae.safetensors', '/workspace/sd-webui-forge-neo/models/text_encoder/clip_l.safetensors', '/workspace/sd-webui-forge-neo/models/text_encoder/t5xxl_fp16.safetensors'], 'unet_storage_dtype': None} [Unload] Trying to free all memory for cuda:0 with 0 models keep loaded ... Done. [Unload] Trying to free all memory for cpu with 0 models keep loaded ... Done. StateDict Keys: {'transformer': 780, 'vae': 244, 'text_encoder': 196, 'text_encoder_2': 220, 'ignore': 0} Using Default T5 Data Type: torch.float16 Working with z of shape (1, 16, 32, 32) = 16384 dimensions. K-Model Created: {'storage_dtype': torch.bfloat16, 'computation_dtype': torch.bfloat16} Model loaded in 7.5s (unload existing model: 0.3s, forge model load: 7.2s). [Unload] Trying to free 2230.25 MB for cuda:0 with 0 models keep loaded ... Done. [Memory Management] Target: IntegratedAutoencoderKL, Free GPU: 30740.62 MB, Model Require: 159.87 MB, Previously Loaded: 0.00 MB, Inference Require: 2038.40 MB, Remaining: 28542.35 MB, Moving model(s) has taken 0.02 seconds Skipping unconditional conditioning when CFG = 1. Negative Prompts are ignored. [Unload] Trying to free 13608.64 MB for cuda:0 with 0 models keep loaded ... Done. [Memory Management] Target: JointTextEncoder, Free GPU: 30569.12 MB, Model Require: 9641.87 MB, Previously Loaded: 0.00 MB, Inference Require: 2038.40 MB, Remaining: 18888.85 MB, Moving model(s) has taken 36.06 seconds Distilled CFG Scale: 3 [Unload] Trying to free 29278.61 MB for cuda:0 with 0 models keep loaded ... Unload model IntegratedAutoencoderKL Unload model JointTextEncoder Done. [Memory Management] Target: KModel, Free GPU: 30704.62 MB, Model Require: 22700.17 MB, Previously Loaded: 0.00 MB, Inference Require: 2038.40 MB, Remaining: 5966.05 MB, Moving model(s) has taken 82.23 seconds 100%|██████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 1/1 [00:01<00:00, 1.68s/it] [Unload] Trying to free 2230.25 MB for cuda:0 with 0 models keep loaded ... Done. | 0/1 [00:00<?, ?it/s] [Memory Management] Target: IntegratedAutoencoderKL, Free GPU: 8002.40 MB, Model Require: 159.87 MB, Previously Loaded: 0.00 MB, Inference Require: 2038.40 MB, Remaining: 5804.13 MB, Moving model(s) has taken 0.02 seconds [-] ADetailer: nothing detected on image 1 with 1st settings. Total progress: 100%|██████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 1/1 [00:00<00:00, 4.46it/s] Total progress: 100%|██████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 1/1 [00:00<00:00, 4.46it/s]

i have all this dependencies: ^C^C^C^C(venv) root@f9b4d6272646:/workspace/sd-webui-forge-neo# pip list Package Version

accelerate 1.10.1 aiofiles 23.2.1 aiohappyeyeballs 2.6.1 aiohttp 3.13.2 aiosignal 1.4.0 annotated-doc 0.0.4 annotated-types 0.7.0 antlr4-python3-runtime 4.9.3 anyio 3.7.1 attrs 25.4.0 brotli 1.2.0 certifi 2025.10.5 charset-normalizer 3.4.4 clean-fid 0.1.35 click 8.3.0 contourpy 1.3.3 cycler 0.12.1 diffusers 0.35.1 diskcache 5.6.3 einops 0.8.1 facexlib 0.3.0 fastapi 0.121.1 ffmpy 0.6.4 filelock 3.20.0 filterpy 1.4.5 fonttools 4.60.1 frozenlist 1.8.0 fsspec 2025.10.0 ftfy 6.3.1 gitdb 4.0.12 GitPython 3.1.44 gradio 4.40.0 gradio_client 1.2.0 gradio_rangeslider 0.0.8 groovy 0.1.2 h11 0.12.0 hf-xet 1.2.0 httpcore 0.15.0 httpx 0.24.1 huggingface-hub 0.34.1 idna 3.11 ImageIO 2.37.2 importlib_metadata 8.7.0 importlib_resources 6.5.2 inflection 0.5.1 Jinja2 3.1.6 joblib 1.5.1 jsonmerge 1.8.0 jsonschema 4.25.1 jsonschema-specifications 2025.9.1 kiwisolver 1.4.9 kornia 0.6.7 lark 1.2.2 lazy_loader 0.4 lightning 2.5.1 lightning-utilities 0.15.2 llvmlite 0.45.1 loadimg 0.1.2 markdown-it-py 4.0.0 MarkupSafe 2.1.5 matplotlib 3.10.7 mdurl 0.1.2 mpmath 1.3.0 multidict 6.7.0 networkx 3.5 numba 0.62.1 numpy 1.26.4 nvidia-cublas-cu12 12.8.4.1 nvidia-cuda-cupti-cu12 12.8.90 nvidia-cuda-nvrtc-cu12 12.8.93 nvidia-cuda-runtime-cu12 12.8.90 nvidia-cudnn-cu12 9.10.2.21 nvidia-cufft-cu12 11.3.3.83 nvidia-cufile-cu12 1.13.1.3 nvidia-curand-cu12 10.3.9.90 nvidia-cusolver-cu12 11.7.3.90 nvidia-cusparse-cu12 12.5.8.93 nvidia-cusparselt-cu12 0.7.1 nvidia-nccl-cu12 2.27.3 nvidia-nvjitlink-cu12 12.8.93 nvidia-nvtx-cu12 12.8.90 omegaconf 2.2.3 open_clip_torch 2.32.0 opencv-python 4.8.1.78 orjson 3.11.4 packaging 24.2 pandas 2.3.3 peft 0.17.1 piexif 1.1.3 pillow 10.4.0 pillow_heif 0.22.0 pip 24.0 polars 1.35.2 polars-runtime-32 1.35.2 propcache 0.4.1 protobuf 4.25.7 psutil 5.9.8 pydantic 2.9.2 pydantic_core 2.23.4 pydub 0.25.1 Pygments 2.19.2 pyparsing 3.2.5 python-dateutil 2.9.0.post0 python-multipart 0.0.20 pytorch-lightning 2.5.6 pytz 2025.2 PyYAML 6.0.3 referencing 0.37.0 regex 2025.11.3 requests 2.32.5 resize-right 0.0.2 rich 14.2.0 rpds-py 0.28.0 ruff 0.14.4 safehttpx 0.1.7 safetensors 0.6.2 sageattention 2.2.0 scikit-image 0.25.2 scipy 1.16.3 semantic-version 2.10.0 setuptools 69.5.1 shellingham 1.5.4 six 1.17.0 smmap 5.0.2 sniffio 1.3.1 spandrel 0.4.1 spandrel_extra_arches 0.2.0 starlette 0.49.3 sympy 1.14.0 tifffile 2025.10.16 timm 1.0.22 tokenizers 0.22.1 tomesd 0.1.3 tomlkit 0.12.0 torch 2.8.0 torchdiffeq 0.2.5 torchmetrics 1.8.2 torchsde 0.2.6 torchvision 0.23.0 tqdm 4.67.1 trampoline 0.1.2 transformers 4.56.2 triton 3.4.0 typer 0.20.0 typing_extensions 4.15.0 tzdata 2025.2 ultralytics 8.3.216 ultralytics-thop 2.0.18 urllib3 2.5.0 uvicorn 0.38.0 wcwidth 0.2.14 websockets 12.0 yarl 1.22.0 zipp 3.23.0

Nov 21 '25 23:11 peepeepeepoopoopoo

I did some tests on my old Nvidia PC (GTX1080) and there Segmentation models work with: ✅Auto1111 Ultralytics: 8.3.203 rich: 14.1.0 mediapipe: 0.10.14 ✅ Forge Ultralytics: 8.3.49 rich: 13.7.1 mediapipe: 0.10.14 ✅ ReForge Ultralytics: 8.3.203 rich: 14.1.0 mediapipe: 0.10.14

Worked not on: ❌ Forge Classic Ultralytics: 8.3.221 rich: 13.9.4 mediapipe 0.10.14

❌ On my AMD PC with Forge Neo it does't worked either: Ultralytics: 8.3.220, 8.3.221, and the new 8.3.222 rich 14.2.0 mediapipe 0.10.14

Everything tested on Python 3.11.9

Downgrading to 8.3.203 worked on Forge classic and neo.

Solution: ⚠️I then tested every Version from 8.3.222 back down until it started to work. ➡️ The latest Version that works for me is: 8.3.216

So something in 8.3.217, that got released 2 weeks ago, broke the compatibility with adetailer.

Used these commands to downgrade (cmd needs to be opened inside the root webui folder): venv\Scripts\activate.bat pip uninstall ultralytics -y pip install ultralytics==8.3.216

Thank you so much, it's work.

Nov 24 '25 15:11 Mastrue