volotat / SD-CN-Animation

This script allows to automate video stylization task using StableDiffusion and ControlNet.
MIT License
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An exception occurred while trying to process the frame: unsupported operand type(s) for +: 'int' and 'NoneType' #185

Open nikolaiusa opened 11 months ago

nikolaiusa commented 11 months ago

vid2vid - ok txt2vid - this error

An exception occurred while trying to process the frame: unsupported operand type(s) for +: 'int' and 'NoneType' Traceback (most recent call last): File "C:\Users\SD\stable-diffusion-webui\extensions\SD-CN-Animation\scripts\base_ui.py", line 146, in process yield from txt2vid.start_process(args) File "C:\Users\SD\stable-diffusion-webui\extensions\SD-CN-Animation\scripts\core\txt2vid.py", line 121, in start_process processedframes, , , = utils.txt2img(args_dict) File "C:\Users\SD\stable-diffusion-webui\extensions\SD-CN-Animation\scripts\core\utils.py", line 380, in txt2img processed = process_images(p) File "C:\Users\SD\stable-diffusion-webui\modules\processing.py", line 673, in process_images res = process_images_inner(p) File "C:\Users\SD\stable-diffusion-webui\extensions\sd-webui-controlnet\scripts\batch_hijack.py", line 42, in processing_process_images_hijack return getattr(processing, '__controlnet_original_process_images_inner')(p, args, kwargs) File "C:\Users\SD\stable-diffusion-webui\modules\processing.py", line 795, in process_images_inner x_samples_ddim = decode_latent_batch(p.sd_model, samples_ddim, target_device=devices.cpu, check_for_nans=True) File "C:\Users\SD\stable-diffusion-webui\modules\processing.py", line 545, in decode_latent_batch sample = decode_first_stage(model, batch[i:i + 1])[0] File "C:\Users\SD\stable-diffusion-webui\modules\processing.py", line 576, in decode_first_stage x = model.decode_first_stage(x.to(devices.dtype_vae)) File "C:\Users\SD\stable-diffusion-webui\modules\sd_hijack_utils.py", line 17, in setattr(resolved_obj, func_path[-1], lambda *args, *kwargs: self(args, kwargs)) File "C:\Users\SD\stable-diffusion-webui\modules\sd_hijack_utils.py", line 28, in call return self.__orig_func(*args, kwargs) File "C:\Users\SD\stable-diffusion-webui\venv\lib\site-packages\torch\utils_contextlib.py", line 115, in decorate_context return func(*args, *kwargs) File "C:\Users\SD\stable-diffusion-webui\repositories\stable-diffusion-stability-ai\ldm\models\diffusion\ddpm.py", line 826, in decode_first_stage return self.first_stage_model.decode(z) File "C:\Users\SD\stable-diffusion-webui\repositories\stable-diffusion-stability-ai\ldm\models\autoencoder.py", line 90, in decode dec = self.decoder(z) File "C:\Users\SD\stable-diffusion-webui\venv\lib\site-packages\torch\nn\modules\module.py", line 1501, in _call_impl return forward_call(args, kwargs) File "C:\Users\SD\stable-diffusion-webui\extensions\multidiffusion-upscaler-for-automatic1111\scripts\vae_optimize.py", line 377, in call if max(H, W) <= self.pad * 2 + self.tile_size: TypeError: unsupported operand type(s) for +: 'int' and 'NoneType'

leonnn1 commented 9 months ago

I got the same error, don't know how to fix it