[Bug] - BLIP interrogation fails w/ " RuntimeError: The size of tensor a (4) must match the size of tensor b (3) at non-singleton dimension 0" - (Use deepbooru works & A1111 naitive BLIP works)

CCpt5 commented 8 months ago

Hey!

First of all I really like the script you've put together here. It seems like a simple idea, but it really adds some spice to IMG2IMG when just playing around w/ images.

I'm experiencing an error whenever I try to use the extension w/o Deepbooru. If that's untoggled the script errors and fails to produce the interrogated prompt. The error I receive is in the attached console log.

I fed the error to Chatgpt-4 which said it seemed to be an image file format issue (having an alpha channel), but I tried resaving images to .jpg which should have removed any extra channels and I still received the same error.

I hope you can take a quick look at this and see if there's a fix for it.

Thanks so much!!

Details

To create a public link, set `share=True` in `launch()`. Startup time: 12.7s (prepare environment: 0.6s, import torch: 1.7s, import gradio: 0.5s, setup paths: 0.3s, initialize shared: 0.1s, other imports: 0.3s, list SD models: 0.2s, load scripts: 4.4s, refresh VAE: 0.1s, create ui: 3.8s, gradio launch: 0.3s, app_started_callback: 0.3s). img2img: load checkpoint from D:\stable-diffusion-webui\models\BLIP\model_base_caption_capfilt_large.pth 100%|████████████████████████████████████████| 890M/890M [00:07<00:00, 128MiB/s] *** Error interrogating Traceback (most recent call last): File "D:\stable-diffusion-webui\modules\interrogate.py", line 194, in interrogate caption = self.generate_caption(pil_image) File "D:\stable-diffusion-webui\modules\interrogate.py", line 174, in generate_caption gpu_image = transforms.Compose([ File "D:\stable-diffusion-webui\venv\lib\site-packages\torchvision\transforms\transforms.py", line 95, in __call__ img = t(img) File "D:\stable-diffusion-webui\venv\lib\site-packages\torch\nn\modules\module.py", line 1518, in _wrapped_call_impl return self._call_impl(*args, **kwargs) File "D:\stable-diffusion-webui\venv\lib\site-packages\torch\nn\modules\module.py", line 1527, in _call_impl return forward_call(*args, **kwargs) File "D:\stable-diffusion-webui\venv\lib\site-packages\torchvision\transforms\transforms.py", line 277, in forward return F.normalize(tensor, self.mean, self.std, self.inplace) File "D:\stable-diffusion-webui\venv\lib\site-packages\torchvision\transforms\functional.py", line 363, in normalize return F_t.normalize(tensor, mean=mean, std=std, inplace=inplace) File "D:\stable-diffusion-webui\venv\lib\site-packages\torchvision\transforms\_functional_tensor.py", line 928, in normalize return tensor.sub_(mean).div_(std) RuntimeError: The size of tensor a (4) must match the size of tensor b (3) at non-singleton dimension 0 --- Prompt: 100%|████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 25/25 [00:05<00:00, 4.81it/s] img2img: *** Error interrogating Traceback (most recent call last): File "D:\stable-diffusion-webui\modules\interrogate.py", line 194, in interrogate caption = self.generate_caption(pil_image) File "D:\stable-diffusion-webui\modules\interrogate.py", line 174, in generate_caption gpu_image = transforms.Compose([ File "D:\stable-diffusion-webui\venv\lib\site-packages\torchvision\transforms\transforms.py", line 95, in __call__ img = t(img) File "D:\stable-diffusion-webui\venv\lib\site-packages\torch\nn\modules\module.py", line 1518, in _wrapped_call_impl return self._call_impl(*args, **kwargs) File "D:\stable-diffusion-webui\venv\lib\site-packages\torch\nn\modules\module.py", line 1527, in _call_impl return forward_call(*args, **kwargs) File "D:\stable-diffusion-webui\venv\lib\site-packages\torchvision\transforms\transforms.py", line 277, in forward return F.normalize(tensor, self.mean, self.std, self.inplace) File "D:\stable-diffusion-webui\venv\lib\site-packages\torchvision\transforms\functional.py", line 363, in normalize return F_t.normalize(tensor, mean=mean, std=std, inplace=inplace) File "D:\stable-diffusion-webui\venv\lib\site-packages\torchvision\transforms\_functional_tensor.py", line 928, in normalize return tensor.sub_(mean).div_(std) RuntimeError: The size of tensor a (4) must match the size of tensor b (3) at non-singleton dimension 0 --- Prompt: 100%|████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 25/25 [00:04<00:00, 5.23it/s] img2img: Prompt: 1boy, 3d, backwards hat, baseball cap, beard, blurry, blurry background, blurry foreground, building, depth of field, dog tags, facial hair, hat, jewelry, male focus, mustache, necklace, photo \(medium\), photo background, realistic, shirt, solo, upper body 100%|████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 25/25 [00:04<00:00, 5.20it/s] img2img: *** Error interrogating Traceback (most recent call last): File "D:\stable-diffusion-webui\modules\interrogate.py", line 194, in interrogate caption = self.generate_caption(pil_image) File "D:\stable-diffusion-webui\modules\interrogate.py", line 174, in generate_caption gpu_image = transforms.Compose([ File "D:\stable-diffusion-webui\venv\lib\site-packages\torchvision\transforms\transforms.py", line 95, in __call__ img = t(img) File "D:\stable-diffusion-webui\venv\lib\site-packages\torch\nn\modules\module.py", line 1518, in _wrapped_call_impl return self._call_impl(*args, **kwargs) File "D:\stable-diffusion-webui\venv\lib\site-packages\torch\nn\modules\module.py", line 1527, in _call_impl return forward_call(*args, **kwargs) File "D:\stable-diffusion-webui\venv\lib\site-packages\torchvision\transforms\transforms.py", line 277, in forward return F.normalize(tensor, self.mean, self.std, self.inplace) File "D:\stable-diffusion-webui\venv\lib\site-packages\torchvision\transforms\functional.py", line 363, in normalize return F_t.normalize(tensor, mean=mean, std=std, inplace=inplace) File "D:\stable-diffusion-webui\venv\lib\site-packages\torchvision\transforms\_functional_tensor.py", line 928, in normalize return tensor.sub_(mean).div_(std) RuntimeError: The size of tensor a (4) must match the size of tensor b (3) at non-singleton dimension 0 --- Prompt: 100%|████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 25/25 [00:04<00:00, 5.21it/s]

System Settings

Details

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Alvi-alvarez commented 7 months ago

I think it is solved cb9ab96

CCpt5 commented 7 months ago

Yes! It works again now. Thank you for your time - I enjoy this extension a lot.

console confirmation of OK

Details

Running on local URL: http://127.0.0.1:7860 To create a public link, set `share=True` in `launch()`. Startup time: 9.7s (prepare environment: 1.7s, import torch: 1.8s, import gradio: 0.5s, setup paths: 0.3s, other imports: 0.3s, list SD models: 0.2s, load scripts: 3.5s, refresh VAE: 0.1s, create ui: 0.9s, gradio launch: 0.2s). Using pytorch attention in VAE Working with z of shape (1, 4, 32, 32) = 4096 dimensions. Using pytorch attention in VAE extra {'cond_stage_model.clip_l.text_projection', 'cond_stage_model.clip_l.transformer.text_model.embeddings.position_ids', 'cond_stage_model.clip_l.logit_scale', 'cond_stage_model.clip_g.transformer.text_model.embeddings.position_ids'} left over keys: dict_keys(['alphas_cumprod', 'alphas_cumprod_prev', 'betas', 'log_one_minus_alphas_cumprod', 'posterior_log_variance_clipped', 'posterior_mean_coef1', 'posterior_mean_coef2', 'posterior_variance', 'sqrt_alphas_cumprod', 'sqrt_one_minus_alphas_cumprod', 'sqrt_recip_alphas_cumprod', 'sqrt_recipm1_alphas_cumprod']) To load target model SDXLClipModel Begin to load 1 model Moving model(s) has taken 0.29 seconds Model loaded in 4.4s (load weights from disk: 0.5s, forge load real models: 3.0s, load VAE: 0.5s, calculate empty prompt: 0.4s). Downloading: "https://github.com/AUTOMATIC1111/TorchDeepDanbooru/releases/download/v1/model-resnet_custom_v3.pt" to D:\stable-diffusion-webui-forge\models\torch_deepdanbooru\model-resnet_custom_v3.pt 100%|██████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 614M/614M [00:05<00:00, 118MB/s] To load target model DeepDanbooruModel Begin to load 1 model Prompt: topnotch artstyle , (couch, day, flower pot, leaf, no humans, palm tree, plant, potted plant, scenery, sunset, tiles, tree, vines, window:0.5) To load target model AutoencoderKL Begin to load 1 model To load target model SDXL Begin to load 1 model Moving model(s) has taken 0.97 seconds 100%|████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 33/33 [00:06<00:00, 4.98it/s] Total progress: 100%|████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 33/33 [00:06<00:00, 4.78it/s] Error parsing "sv_negative: "████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 33/33 [00:06<00:00, 6.58it/s] load checkpoint from D:\stable-diffusion-webui-forge\models\BLIP\model_base_caption_capfilt_large.pth To load target model BLIP_Decoder To load target model CLIP Begin to load 2 models Moving model(s) has taken 0.19 seconds Prompt: topnotch artstyle , (a living room with a large couch and a large window with a view of the city outside of it, Evgeny Lushpin, unreal engine 5 highly rendered, a photorealistic painting, photorealism:0.5) 100%|████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 33/33 [00:05<00:00, 5.62it/s] Total progress: 33it [00:06, 5.00it/s] Total progress: 33it [00:06, 6.64it/s]

CCpt5 commented 7 months ago

I think it is solved cb9ab96

Actually, it worked for a session but now I'm getting the below error. Perhaps I need to clear an old config file? (Deepbooru still works fine)

Python 3.10.6 (tags/v3.10.6:9c7b4bd, Aug  1 2022, 21:53:49) [MSC v.1932 64 bit (AMD64)]
Version: v1.7.0-455-gd69a7944
Commit hash: d69a7944c9ad5a086d99cf9220a3a2742a1194f3
Launching Web UI with arguments: --opt-sdp-attention --no-half-vae --opt-channelslast --skip-torch-cuda-test --skip-version-check --ckpt-dir e:\Stable Diffusion Checkpoints
no module 'xformers'. Processing without...
no module 'xformers'. Processing without...
No module 'xformers'. Proceeding without it.
ControlNet preprocessor location: D:\stable-diffusion-webui\extensions\3sd-webui-controlnet\annotator\downloads
2024-02-10 22:45:04,285 - ControlNet - INFO - ControlNet v1.1.440
2024-02-10 22:45:04,344 - ControlNet - INFO - ControlNet v1.1.440
[-] ADetailer initialized. version: 24.1.2, num models: 9
Tag Autocomplete: Could not locate model-keyword extension, Lora trigger word completion will be limited to those added through the extra networks menu.
Loading weights [31e35c80fc] from e:\Stable Diffusion Checkpoints\z-base-models\sd_xl_base_1.0.safetensors
Creating model from config: D:\stable-diffusion-webui\repositories\generative-models\configs\inference\sd_xl_base.yaml
Applying attention optimization: sdp... done.
Model loaded in 2.5s (load weights from disk: 0.1s, create model: 0.2s, apply weights to model: 1.9s, calculate empty prompt: 0.1s).
2024-02-10 22:45:08,651 - ControlNet - INFO - ControlNet UI callback registered.
Running on local URL:  http://127.0.0.1:7860

To create a public link, set `share=True` in `launch()`.
Startup time: 9.5s (prepare environment: 0.6s, import torch: 1.4s, import gradio: 0.5s, setup paths: 0.4s, initialize shared: 0.1s, other imports: 0.2s, list SD models: 0.2s, load scripts: 2.2s, refresh VAE: 0.1s, create ui: 3.2s, gradio launch: 0.2s, app_started_callback: 0.2s).
*** Error interrogating
    Traceback (most recent call last):
      File "D:\stable-diffusion-webui\modules\interrogate.py", line 192, in interrogate
        self.load()
      File "D:\stable-diffusion-webui\modules\interrogate.py", line 121, in load
        self.blip_model = self.load_blip_model()
      File "D:\stable-diffusion-webui\modules\interrogate.py", line 101, in load_blip_model
        blip_model = models.blip.blip_decoder(pretrained=files[0], image_size=blip_image_eval_size, vit='base', med_config=os.path.join(paths.paths["BLIP"], "configs", "med_config.json"))
      File "D:\stable-diffusion-webui\repositories\BLIP\models\blip.py", line 173, in blip_decoder
        model = BLIP_Decoder(**kwargs)
      File "D:\stable-diffusion-webui\repositories\BLIP\models\blip.py", line 96, in __init__
        self.tokenizer = init_tokenizer()
      File "D:\stable-diffusion-webui\repositories\BLIP\models\blip.py", line 187, in init_tokenizer
        tokenizer = BertTokenizer.from_pretrained('bert-base-uncased')
      File "D:\stable-diffusion-webui\venv\lib\site-packages\transformers\tokenization_utils_base.py", line 1825, in from_pretrained
        return cls._from_pretrained(
      File "D:\stable-diffusion-webui\venv\lib\site-packages\transformers\tokenization_utils_base.py", line 1876, in _from_pretrained
        init_kwargs = json.load(tokenizer_config_handle)
      File "C:\Users\Copperpot\AppData\Local\Programs\Python\Python310\lib\json\__init__.py", line 293, in load
        return loads(fp.read(),
      File "C:\Users\Copperpot\AppData\Local\Programs\Python\Python310\lib\json\__init__.py", line 346, in loads
        return _default_decoder.decode(s)
      File "C:\Users\Copperpot\AppData\Local\Programs\Python\Python310\lib\json\decoder.py", line 337, in decode
        obj, end = self.raw_decode(s, idx=_w(s, 0).end())
      File "C:\Users\Copperpot\AppData\Local\Programs\Python\Python310\lib\json\decoder.py", line 355, in raw_decode
        raise JSONDecodeError("Expecting value", s, err.value) from None
    json.decoder.JSONDecodeError: Expecting value: line 1 column 1 (char 0)

---
Prompt: test, (<error>:0.5)
100%|████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 25/25 [00:04<00:00,  5.59it/s]
Total progress: 25it [00:05,  4.96it/s]
Total progress: 25it [00:05,  5.87it/s]

CCpt5 commented 7 months ago

I'm getting the same error from Loopback when I set it to append interrogation (BLIP) - so must be something on my end. I'll work on it (clearing cache files/etc). Thx again.

Alvi-alvarez / sd-Img2img-batch-interrogator

[Bug] - BLIP interrogation fails w/ " RuntimeError: The size of tensor a (4) must match the size of tensor b (3) at non-singleton dimension 0" - (Use deepbooru works & A1111 naitive BLIP works) #4