Repository: stable-diffusion-webui
Issue: [Bug]: Seems like img2img does not take the image I uploaded.
Labels: bug-report

### Checklist

- [ ] The issue exists after disabling all extensions
- [X] The issue exists on a clean installation of webui
- [ ] The issue is caused by an extension, but I believe it is caused by a bug in the webui
- [X] The issue exists in the current version of the webui
- [X] The issue has not been reported before recently
- [ ] The issue has been reported before but has not been fixed yet

### What happened?

Seems like img2img does not take the image I uploaded and just generates whet I prompted.
For example a picture of an astronaut on a Llama is the picture while the prompt is add flowers.

### Steps to reproduce the problem

1. Go to img2img
2.  Upload an existing image (in this case "an astronaut on a Llama") 
3. In the prompt type "add flowers"
4. Click Generate.

### What should have happened?

It should have added flowers in the background of the exisiting photo

### What browsers do you use to access the UI ?

Google Chrome

### Sysinfo

{
    "Platform": "Windows-10-10.0.22621-SP0",
    "Python": "3.10.6",
    "Version": "v1.7.0",
    "Commit": "cf2772fab0af5573da775e7437e6acdca424f26e",
    "Script path": "C:\\Users\\user\\Downloads\\sd.webui\\webui",
    "Data path": "C:\\Users\\user\\Downloads\\sd.webui\\webui",
    "Extensions dir": "C:\\Users\\user\\Downloads\\sd.webui\\webui\\extensions",
    "Checksum": "5eaba2e0599f50d2be4671f4db2849df158c7d761168d3e01afe49c35d0897d8",
    "Commandline": [
        "launch.py"
    ],
    "Torch env info": {
        "torch_version": "2.0.1+cu118",
        "is_debug_build": "False",
        "cuda_compiled_version": "11.8",
        "gcc_version": null,
        "clang_version": null,
        "cmake_version": null,
        "os": "Microsoft Windows 11 Pro",
        "libc_version": "N/A",
        "python_version": "3.10.6 (tags/v3.10.6:9c7b4bd, Aug  1 2022, 21:53:49) [MSC v.1932 64 bit (AMD64)] (64-bit runtime)",
        "python_platform": "Windows-10-10.0.22621-SP0",
        "is_cuda_available": "True",
        "cuda_runtime_version": null,
        "cuda_module_loading": "LAZY",
        "nvidia_driver_version": "537.42",
        "nvidia_gpu_models": "GPU 0: NVIDIA GeForce RTX 3080",
        "cudnn_version": null,
        "pip_version": "pip3",
        "pip_packages": [
            "numpy==1.23.5",
            "open-clip-torch==2.20.0",
            "pytorch-lightning==1.9.4",
            "torch==2.0.1+cu118",
            "torchdiffeq==0.2.3",
            "torchmetrics==1.2.1",
            "torchsde==0.2.6",
            "torchvision==0.15.2+cu118"
        ],
        "conda_packages": null,
        "hip_compiled_version": "N/A",
        "hip_runtime_version": "N/A",
        "miopen_runtime_version": "N/A",
        "caching_allocator_config": "",
        "is_xnnpack_available": "True",
        "cpu_info": [
            "Architecture=9",
            "CurrentClockSpeed=3801",
            "DeviceID=CPU0",
            "Family=198",
            "L2CacheSize=2048",
            "L2CacheSpeed=",
            "Manufacturer=GenuineIntel",
            "MaxClockSpeed=3801",
            "Name=Intel(R) Core(TM) i7-10700K CPU @ 3.80GHz",
            "ProcessorType=3",
            "Revision="
        ]
    },
    "Exceptions": [
        {
            "exception": "A tensor with all NaNs was produced in Unet. This could be either because there's not enough precision to represent the picture, or because your video card does not support half type. Try setting the \"Upcast cross attention layer to float32\" option in Settings > Stable Diffusion or using the --no-half commandline argument to fix this. Use --disable-nan-check commandline argument to disable this check.",
            "traceback": [
                [
                    "C:\\Users\\user\\Downloads\\sd.webui\\webui\\modules\\call_queue.py, line 57, f",
                    "res = list(func(*args, **kwargs))"
                ],
                [
                    "C:\\Users\\user\\Downloads\\sd.webui\\webui\\modules\\call_queue.py, line 36, f",
                    "res = func(*args, **kwargs)"
                ],
                [
                    "C:\\Users\\user\\Downloads\\sd.webui\\webui\\modules\\txt2img.py, line 55, txt2img",
                    "processed = processing.process_images(p)"
                ],
                [
                    "C:\\Users\\user\\Downloads\\sd.webui\\webui\\modules\\processing.py, line 734, process_images",
                    "res = process_images_inner(p)"
                ],
                [
                    "C:\\Users\\user\\Downloads\\sd.webui\\webui\\modules\\processing.py, line 868, process_images_inner",
                    "samples_ddim = p.sample(conditioning=p.c, unconditional_conditioning=p.uc, seeds=p.seeds, subseeds=p.subseeds, subseed_strength=p.subseed_strength, prompts=p.prompts)"
                ],
                [
                    "C:\\Users\\user\\Downloads\\sd.webui\\webui\\modules\\processing.py, line 1142, sample",
                    "samples = self.sampler.sample(self, x, conditioning, unconditional_conditioning, image_conditioning=self.txt2img_image_conditioning(x))"
                ],
                [
                    "C:\\Users\\user\\Downloads\\sd.webui\\webui\\modules\\sd_samplers_kdiffusion.py, line 235, sample",
                    "samples = self.launch_sampling(steps, lambda: self.func(self.model_wrap_cfg, x, extra_args=self.sampler_extra_args, disable=False, callback=self.callback_state, **extra_params_kwargs))"
                ],
                [
                    "C:\\Users\\user\\Downloads\\sd.webui\\webui\\modules\\sd_samplers_common.py, line 261, launch_sampling",
                    "return func()"
                ],
                [
                    "C:\\Users\\user\\Downloads\\sd.webui\\webui\\modules\\sd_samplers_kdiffusion.py, line 235, <lambda>",
                    "samples = self.launch_sampling(steps, lambda: self.func(self.model_wrap_cfg, x, extra_args=self.sampler_extra_args, disable=False, callback=self.callback_state, **extra_params_kwargs))"
                ],
                [
                    "C:\\Users\\user\\Downloads\\sd.webui\\system\\python\\lib\\site-packages\\torch\\utils\\_contextlib.py, line 115, decorate_context",
                    "return func(*args, **kwargs)"
                ],
                [
                    "C:\\Users\\user\\Downloads\\sd.webui\\webui\\repositories\\k-diffusion\\k_diffusion\\sampling.py, line 594, sample_dpmpp_2m",
                    "denoised = model(x, sigmas[i] * s_in, **extra_args)"
                ],
                [
                    "C:\\Users\\user\\Downloads\\sd.webui\\system\\python\\lib\\site-packages\\torch\\nn\\modules\\module.py, line 1501, _call_impl",
                    "return forward_call(*args, **kwargs)"
                ],
                [
                    "C:\\Users\\user\\Downloads\\sd.webui\\webui\\modules\\sd_samplers_cfg_denoiser.py, line 201, forward",
                    "devices.test_for_nans(x_out, \"unet\")"
                ],
                [
                    "C:\\Users\\user\\Downloads\\sd.webui\\webui\\modules\\devices.py, line 150, test_for_nans",
                    "raise NansException(message)"
                ]
            ]
        },
        {
            "exception": "A tensor with all NaNs was produced in Unet. This could be either because there's not enough precision to represent the picture, or because your video card does not support half type. Try setting the \"Upcast cross attention layer to float32\" option in Settings > Stable Diffusion or using the --no-half commandline argument to fix this. Use --disable-nan-check commandline argument to disable this check.",
            "traceback": [
                [
                    "C:\\Users\\user\\Downloads\\sd.webui\\webui\\modules\\call_queue.py, line 57, f",
                    "res = list(func(*args, **kwargs))"
                ],
                [
                    "C:\\Users\\user\\Downloads\\sd.webui\\webui\\modules\\call_queue.py, line 36, f",
                    "res = func(*args, **kwargs)"
                ],
                [
                    "C:\\Users\\user\\Downloads\\sd.webui\\webui\\modules\\txt2img.py, line 55, txt2img",
                    "processed = processing.process_images(p)"
                ],
                [
                    "C:\\Users\\user\\Downloads\\sd.webui\\webui\\modules\\processing.py, line 734, process_images",
                    "res = process_images_inner(p)"
                ],
                [
                    "C:\\Users\\user\\Downloads\\sd.webui\\webui\\modules\\processing.py, line 868, process_images_inner",
                    "samples_ddim = p.sample(conditioning=p.c, unconditional_conditioning=p.uc, seeds=p.seeds, subseeds=p.subseeds, subseed_strength=p.subseed_strength, prompts=p.prompts)"
                ],
                [
                    "C:\\Users\\user\\Downloads\\sd.webui\\webui\\modules\\processing.py, line 1142, sample",
                    "samples = self.sampler.sample(self, x, conditioning, unconditional_conditioning, image_conditioning=self.txt2img_image_conditioning(x))"
                ],
                [
                    "C:\\Users\\user\\Downloads\\sd.webui\\webui\\modules\\sd_samplers_kdiffusion.py, line 235, sample",
                    "samples = self.launch_sampling(steps, lambda: self.func(self.model_wrap_cfg, x, extra_args=self.sampler_extra_args, disable=False, callback=self.callback_state, **extra_params_kwargs))"
                ],
                [
                    "C:\\Users\\user\\Downloads\\sd.webui\\webui\\modules\\sd_samplers_common.py, line 261, launch_sampling",
                    "return func()"
                ],
                [
                    "C:\\Users\\user\\Downloads\\sd.webui\\webui\\modules\\sd_samplers_kdiffusion.py, line 235, <lambda>",
                    "samples = self.launch_sampling(steps, lambda: self.func(self.model_wrap_cfg, x, extra_args=self.sampler_extra_args, disable=False, callback=self.callback_state, **extra_params_kwargs))"
                ],
                [
                    "C:\\Users\\user\\Downloads\\sd.webui\\system\\python\\lib\\site-packages\\torch\\utils\\_contextlib.py, line 115, decorate_context",
                    "return func(*args, **kwargs)"
                ],
                [
                    "C:\\Users\\user\\Downloads\\sd.webui\\webui\\repositories\\k-diffusion\\k_diffusion\\sampling.py, line 594, sample_dpmpp_2m",
                    "denoised = model(x, sigmas[i] * s_in, **extra_args)"
                ],
                [
                    "C:\\Users\\user\\Downloads\\sd.webui\\system\\python\\lib\\site-packages\\torch\\nn\\modules\\module.py, line 1501, _call_impl",
                    "return forward_call(*args, **kwargs)"
                ],
                [
                    "C:\\Users\\user\\Downloads\\sd.webui\\webui\\modules\\sd_samplers_cfg_denoiser.py, line 201, forward",
                    "devices.test_for_nans(x_out, \"unet\")"
                ],
                [
                    "C:\\Users\\user\\Downloads\\sd.webui\\webui\\modules\\devices.py, line 150, test_for_nans",
                    "raise NansException(message)"
                ]
            ]
        },
        {
            "exception": "A tensor with all NaNs was produced in Unet. This could be either because there's not enough precision to represent the picture, or because your video card does not support half type. Try setting the \"Upcast cross attention layer to float32\" option in Settings > Stable Diffusion or using the --no-half commandline argument to fix this. Use --disable-nan-check commandline argument to disable this check.",
            "traceback": [
                [
                    "C:\\Users\\user\\Downloads\\sd.webui\\webui\\modules\\call_queue.py, line 57, f",
                    "res = list(func(*args, **kwargs))"
                ],
                [
                    "C:\\Users\\user\\Downloads\\sd.webui\\webui\\modules\\call_queue.py, line 36, f",
                    "res = func(*args, **kwargs)"
                ],
                [
                    "C:\\Users\\user\\Downloads\\sd.webui\\webui\\modules\\txt2img.py, line 55, txt2img",
                    "processed = processing.process_images(p)"
                ],
                [
                    "C:\\Users\\user\\Downloads\\sd.webui\\webui\\modules\\processing.py, line 734, process_images",
                    "res = process_images_inner(p)"
                ],
                [
                    "C:\\Users\\user\\Downloads\\sd.webui\\webui\\modules\\processing.py, line 868, process_images_inner",
                    "samples_ddim = p.sample(conditioning=p.c, unconditional_conditioning=p.uc, seeds=p.seeds, subseeds=p.subseeds, subseed_strength=p.subseed_strength, prompts=p.prompts)"
                ],
                [
                    "C:\\Users\\user\\Downloads\\sd.webui\\webui\\modules\\processing.py, line 1142, sample",
                    "samples = self.sampler.sample(self, x, conditioning, unconditional_conditioning, image_conditioning=self.txt2img_image_conditioning(x))"
                ],
                [
                    "C:\\Users\\user\\Downloads\\sd.webui\\webui\\modules\\sd_samplers_kdiffusion.py, line 235, sample",
                    "samples = self.launch_sampling(steps, lambda: self.func(self.model_wrap_cfg, x, extra_args=self.sampler_extra_args, disable=False, callback=self.callback_state, **extra_params_kwargs))"
                ],
                [
                    "C:\\Users\\user\\Downloads\\sd.webui\\webui\\modules\\sd_samplers_common.py, line 261, launch_sampling",
                    "return func()"
                ],
                [
                    "C:\\Users\\user\\Downloads\\sd.webui\\webui\\modules\\sd_samplers_kdiffusion.py, line 235, <lambda>",
                    "samples = self.launch_sampling(steps, lambda: self.func(self.model_wrap_cfg, x, extra_args=self.sampler_extra_args, disable=False, callback=self.callback_state, **extra_params_kwargs))"
                ],
                [
                    "C:\\Users\\user\\Downloads\\sd.webui\\system\\python\\lib\\site-packages\\torch\\utils\\_contextlib.py, line 115, decorate_context",
                    "return func(*args, **kwargs)"
                ],
                [
                    "C:\\Users\\user\\Downloads\\sd.webui\\webui\\repositories\\k-diffusion\\k_diffusion\\sampling.py, line 594, sample_dpmpp_2m",
                    "denoised = model(x, sigmas[i] * s_in, **extra_args)"
                ],
                [
                    "C:\\Users\\user\\Downloads\\sd.webui\\system\\python\\lib\\site-packages\\torch\\nn\\modules\\module.py, line 1501, _call_impl",
                    "return forward_call(*args, **kwargs)"
                ],
                [
                    "C:\\Users\\user\\Downloads\\sd.webui\\webui\\modules\\sd_samplers_cfg_denoiser.py, line 201, forward",
                    "devices.test_for_nans(x_out, \"unet\")"
                ],
                [
                    "C:\\Users\\user\\Downloads\\sd.webui\\webui\\modules\\devices.py, line 150, test_for_nans",
                    "raise NansException(message)"
                ]
            ]
        },
        {
            "exception": "A tensor with all NaNs was produced in Unet. This could be either because there's not enough precision to represent the picture, or because your video card does not support half type. Try setting the \"Upcast cross attention layer to float32\" option in Settings > Stable Diffusion or using the --no-half commandline argument to fix this. Use --disable-nan-check commandline argument to disable this check.",
            "traceback": [
                [
                    "C:\\Users\\user\\Downloads\\sd.webui\\webui\\modules\\call_queue.py, line 57, f",
                    "res = list(func(*args, **kwargs))"
                ],
                [
                    "C:\\Users\\user\\Downloads\\sd.webui\\webui\\modules\\call_queue.py, line 36, f",
                    "res = func(*args, **kwargs)"
                ],
                [
                    "C:\\Users\\user\\Downloads\\sd.webui\\webui\\modules\\txt2img.py, line 55, txt2img",
                    "processed = processing.process_images(p)"
                ],
                [
                    "C:\\Users\\user\\Downloads\\sd.webui\\webui\\modules\\processing.py, line 734, process_images",
                    "res = process_images_inner(p)"
                ],
                [
                    "C:\\Users\\user\\Downloads\\sd.webui\\webui\\modules\\processing.py, line 868, process_images_inner",
                    "samples_ddim = p.sample(conditioning=p.c, unconditional_conditioning=p.uc, seeds=p.seeds, subseeds=p.subseeds, subseed_strength=p.subseed_strength, prompts=p.prompts)"
                ],
                [
                    "C:\\Users\\user\\Downloads\\sd.webui\\webui\\modules\\processing.py, line 1142, sample",
                    "samples = self.sampler.sample(self, x, conditioning, unconditional_conditioning, image_conditioning=self.txt2img_image_conditioning(x))"
                ],
                [
                    "C:\\Users\\user\\Downloads\\sd.webui\\webui\\modules\\sd_samplers_kdiffusion.py, line 235, sample",
                    "samples = self.launch_sampling(steps, lambda: self.func(self.model_wrap_cfg, x, extra_args=self.sampler_extra_args, disable=False, callback=self.callback_state, **extra_params_kwargs))"
                ],
                [
                    "C:\\Users\\user\\Downloads\\sd.webui\\webui\\modules\\sd_samplers_common.py, line 261, launch_sampling",
                    "return func()"
                ],
                [
                    "C:\\Users\\user\\Downloads\\sd.webui\\webui\\modules\\sd_samplers_kdiffusion.py, line 235, <lambda>",
                    "samples = self.launch_sampling(steps, lambda: self.func(self.model_wrap_cfg, x, extra_args=self.sampler_extra_args, disable=False, callback=self.callback_state, **extra_params_kwargs))"
                ],
                [
                    "C:\\Users\\user\\Downloads\\sd.webui\\system\\python\\lib\\site-packages\\torch\\utils\\_contextlib.py, line 115, decorate_context",
                    "return func(*args, **kwargs)"
                ],
                [
                    "C:\\Users\\user\\Downloads\\sd.webui\\webui\\repositories\\k-diffusion\\k_diffusion\\sampling.py, line 594, sample_dpmpp_2m",
                    "denoised = model(x, sigmas[i] * s_in, **extra_args)"
                ],
                [
                    "C:\\Users\\user\\Downloads\\sd.webui\\system\\python\\lib\\site-packages\\torch\\nn\\modules\\module.py, line 1501, _call_impl",
                    "return forward_call(*args, **kwargs)"
                ],
                [
                    "C:\\Users\\user\\Downloads\\sd.webui\\webui\\modules\\sd_samplers_cfg_denoiser.py, line 201, forward",
                    "devices.test_for_nans(x_out, \"unet\")"
                ],
                [
                    "C:\\Users\\user\\Downloads\\sd.webui\\webui\\modules\\devices.py, line 150, test_for_nans",
                    "raise NansException(message)"
                ]
            ]
        },
        {
            "exception": "A tensor with all NaNs was produced in Unet. This could be either because there's not enough precision to represent the picture, or because your video card does not support half type. Try setting the \"Upcast cross attention layer to float32\" option in Settings > Stable Diffusion or using the --no-half commandline argument to fix this. Use --disable-nan-check commandline argument to disable this check.",
            "traceback": [
                [
                    "C:\\Users\\user\\Downloads\\sd.webui\\webui\\modules\\call_queue.py, line 57, f",
                    "res = list(func(*args, **kwargs))"
                ],
                [
                    "C:\\Users\\user\\Downloads\\sd.webui\\webui\\modules\\call_queue.py, line 36, f",
                    "res = func(*args, **kwargs)"
                ],
                [
                    "C:\\Users\\user\\Downloads\\sd.webui\\webui\\modules\\txt2img.py, line 55, txt2img",
                    "processed = processing.process_images(p)"
                ],
                [
                    "C:\\Users\\user\\Downloads\\sd.webui\\webui\\modules\\processing.py, line 734, process_images",
                    "res = process_images_inner(p)"
                ],
                [
                    "C:\\Users\\user\\Downloads\\sd.webui\\webui\\modules\\processing.py, line 868, process_images_inner",
                    "samples_ddim = p.sample(conditioning=p.c, unconditional_conditioning=p.uc, seeds=p.seeds, subseeds=p.subseeds, subseed_strength=p.subseed_strength, prompts=p.prompts)"
                ],
                [
                    "C:\\Users\\user\\Downloads\\sd.webui\\webui\\modules\\processing.py, line 1142, sample",
                    "samples = self.sampler.sample(self, x, conditioning, unconditional_conditioning, image_conditioning=self.txt2img_image_conditioning(x))"
                ],
                [
                    "C:\\Users\\user\\Downloads\\sd.webui\\webui\\modules\\sd_samplers_kdiffusion.py, line 235, sample",
                    "samples = self.launch_sampling(steps, lambda: self.func(self.model_wrap_cfg, x, extra_args=self.sampler_extra_args, disable=False, callback=self.callback_state, **extra_params_kwargs))"
                ],
                [
                    "C:\\Users\\user\\Downloads\\sd.webui\\webui\\modules\\sd_samplers_common.py, line 261, launch_sampling",
                    "return func()"
                ],
                [
                    "C:\\Users\\user\\Downloads\\sd.webui\\webui\\modules\\sd_samplers_kdiffusion.py, line 235, <lambda>",
                    "samples = self.launch_sampling(steps, lambda: self.func(self.model_wrap_cfg, x, extra_args=self.sampler_extra_args, disable=False, callback=self.callback_state, **extra_params_kwargs))"
                ],
                [
                    "C:\\Users\\user\\Downloads\\sd.webui\\system\\python\\lib\\site-packages\\torch\\utils\\_contextlib.py, line 115, decorate_context",
                    "return func(*args, **kwargs)"
                ],
                [
                    "C:\\Users\\user\\Downloads\\sd.webui\\webui\\repositories\\k-diffusion\\k_diffusion\\sampling.py, line 594, sample_dpmpp_2m",
                    "denoised = model(x, sigmas[i] * s_in, **extra_args)"
                ],
                [
                    "C:\\Users\\user\\Downloads\\sd.webui\\system\\python\\lib\\site-packages\\torch\\nn\\modules\\module.py, line 1501, _call_impl",
                    "return forward_call(*args, **kwargs)"
                ],
                [
                    "C:\\Users\\user\\Downloads\\sd.webui\\webui\\modules\\sd_samplers_cfg_denoiser.py, line 201, forward",
                    "devices.test_for_nans(x_out, \"unet\")"
                ],
                [
                    "C:\\Users\\user\\Downloads\\sd.webui\\webui\\modules\\devices.py, line 150, test_for_nans",
                    "raise NansException(message)"
                ]
            ]
        }
    ],
    "CPU": {
        "model": "Intel64 Family 6 Model 165 Stepping 5, GenuineIntel",
        "count logical": 16,
        "count physical": 8
    },
    "RAM": {
        "total": "32GB",
        "used": "18GB",
        "free": "14GB"
    },
    "Extensions": [],
    "Inactive extensions": [],
    "Environment": {
        "GRADIO_ANALYTICS_ENABLED": "False"
    },
    "Config": {
        "samples_save": true,
        "samples_format": "png",
        "samples_filename_pattern": "",
        "save_images_add_number": true,
        "save_images_replace_action": "Replace",
        "grid_save": true,
        "grid_format": "png",
        "grid_extended_filename": false,
        "grid_only_if_multiple": true,
        "grid_prevent_empty_spots": false,
        "grid_zip_filename_pattern": "",
        "n_rows": -1,
        "font": "",
        "grid_text_active_color": "#000000",
        "grid_text_inactive_color": "#999999",
        "grid_background_color": "#ffffff",
        "save_images_before_face_restoration": false,
        "save_images_before_highres_fix": false,
        "save_images_before_color_correction": false,
        "save_mask": false,
        "save_mask_composite": false,
        "jpeg_quality": 80,
        "webp_lossless": false,
        "export_for_4chan": true,
        "img_downscale_threshold": 4.0,
        "target_side_length": 4000,
        "img_max_size_mp": 200,
        "use_original_name_batch": true,
        "use_upscaler_name_as_suffix": false,
        "save_selected_only": true,
        "save_init_img": false,
        "temp_dir": "",
        "clean_temp_dir_at_start": false,
        "save_incomplete_images": false,
        "notification_audio": true,
        "notification_volume": 100,
        "outdir_samples": "",
        "outdir_txt2img_samples": "outputs/txt2img-images",
        "outdir_img2img_samples": "outputs/img2img-images",
        "outdir_extras_samples": "outputs/extras-images",
        "outdir_grids": "",
        "outdir_txt2img_grids": "outputs/txt2img-grids",
        "outdir_img2img_grids": "outputs/img2img-grids",
        "outdir_save": "log/images",
        "outdir_init_images": "outputs/init-images",
        "save_to_dirs": true,
        "grid_save_to_dirs": true,
        "use_save_to_dirs_for_ui": false,
        "directories_filename_pattern": "[date]",
        "directories_max_prompt_words": 8,
        "ESRGAN_tile": 192,
        "ESRGAN_tile_overlap": 8,
        "realesrgan_enabled_models": [
            "R-ESRGAN 4x+",
            "R-ESRGAN 4x+ Anime6B"
        ],
        "upscaler_for_img2img": null,
        "face_restoration": false,
        "face_restoration_model": "CodeFormer",
        "code_former_weight": 0.5,
        "face_restoration_unload": false,
        "auto_launch_browser": "Local",
        "enable_console_prompts": false,
        "show_warnings": false,
        "show_gradio_deprecation_warnings": true,
        "memmon_poll_rate": 8,
        "samples_log_stdout": false,
        "multiple_tqdm": true,
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        "dump_stacks_on_signal": false,
        "api_enable_requests": true,
        "api_forbid_local_requests": true,
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        "unload_models_when_training": false,
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        "save_training_settings_to_txt": true,
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        "dataset_filename_join_string": " ",
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        "training_xattention_optimizations": false,
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        "sd_checkpoints_limit": 1,
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        "enable_emphasis": true,
        "enable_batch_seeds": true,
        "comma_padding_backtrack": 20,
        "CLIP_stop_at_last_layers": 1,
        "upcast_attn": true,
        "randn_source": "GPU",
        "tiling": false,
        "hires_fix_refiner_pass": "first pass",
        "sdxl_crop_top": 0,
        "sdxl_crop_left": 0,
        "sdxl_refiner_low_aesthetic_score": 2.5,
        "sdxl_refiner_high_aesthetic_score": 6.0,
        "sd_vae_checkpoint_cache": 0,
        "sd_vae": "Automatic",
        "sd_vae_overrides_per_model_preferences": true,
        "auto_vae_precision": true,
        "sd_vae_encode_method": "Full",
        "sd_vae_decode_method": "Full",
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        "img2img_inpaint_mask_brush_color": "#ffffff",
        "img2img_inpaint_sketch_default_brush_color": "#ffffff",
        "return_mask": false,
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        "s_min_uncond": 0.0,
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        "use_old_karras_scheduler_sigmas": false,
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        "interrogate_keep_models_in_memory": false,
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        "extra_networks_add_text_separator": " ",
        "ui_extra_networks_tab_reorder": "",
        "textual_inversion_print_at_load": false,
        "textual_inversion_add_hashes_to_infotext": true,
        "sd_hypernetwork": "None",
        "keyedit_precision_attention": 0.1,
        "keyedit_precision_extra": 0.05,
        "keyedit_delimiters": ".,\\/!?%^*;:{}=`~() ",
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            "Carriage Return",
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        ],
        "keyedit_move": true,
        "disable_token_counters": false,
        "return_grid": true,
        "do_not_show_images": false,
        "js_modal_lightbox": true,
        "js_modal_lightbox_initially_zoomed": true,
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        "js_modal_lightbox_gamepad_repeat": 250,
        "gallery_height": "",
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        "samplers_in_dropdown": true,
        "dimensions_and_batch_together": true,
        "sd_checkpoint_dropdown_use_short": false,
        "hires_fix_show_sampler": false,
        "hires_fix_show_prompts": false,
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        "img2img_settings_accordion": false,
        "localization": "None",
        "quicksettings_list": [
            "sd_model_checkpoint"
        ],
        "ui_tab_order": [],
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        "ui_reorder_list": [],
        "gradio_theme": "Default",
        "gradio_themes_cache": true,
        "show_progress_in_title": true,
        "send_seed": true,
        "send_size": true,
        "enable_pnginfo": true,
        "save_txt": false,
        "add_model_name_to_info": true,
        "add_model_hash_to_info": true,
        "add_vae_name_to_info": true,
        "add_vae_hash_to_info": true,
        "add_user_name_to_info": false,
        "add_version_to_infotext": true,
        "disable_weights_auto_swap": true,
        "infotext_skip_pasting": [],
        "infotext_styles": "Apply if any",
        "show_progressbar": true,
        "live_previews_enable": true,
        "live_previews_image_format": "png",
        "show_progress_grid": true,
        "show_progress_every_n_steps": 10,
        "show_progress_type": "Approx NN",
        "live_preview_allow_lowvram_full": false,
        "live_preview_content": "Prompt",
        "live_preview_refresh_period": 1000,
        "live_preview_fast_interrupt": false,
        "js_live_preview_in_modal_lightbox": false,
        "hide_samplers": [],
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        "sd_lora": "None",
        "lora_preferred_name": "Alias from file",
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        "lora_hide_unknown_for_versions": [],
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        "extra_options_txt2img": [],
        "extra_options_img2img": [],
        "extra_options_cols": 1,
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        "canvas_hotkey_zoom": "Alt",
        "canvas_hotkey_adjust": "Ctrl",
        "canvas_hotkey_move": "F",
        "canvas_hotkey_fullscreen": "S",
        "canvas_hotkey_reset": "R",
        "canvas_hotkey_overlap": "O",
        "canvas_show_tooltip": true,
        "canvas_auto_expand": true,
        "canvas_blur_prompt": false,
        "canvas_disabled_functions": [
            "Overlap"
        ]
    },
    "Startup": {
        "total": 0.6985111236572266,
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            "list SD models": 0.0019979476928710938,
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            "load scripts/custom_code.py": 0.006000518798828125,
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            "load scripts/postprocessing_codeformer.py": 0.0009999275207519531,
            "load scripts/postprocessing_create_flipped_copies.py": 0.0010008811950683594,
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            "load scripts/postprocessing_gfpgan.py": 0.00118255615234375,
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            "load scripts/postprocessing_upscale.py": 0.0010259151458740234,
            "load scripts/processing_autosized_crop.py": 0.0009996891021728516,
            "load scripts/prompt_matrix.py": 0.0,
            "load scripts/prompts_from_file.py": 0.0010008811950683594,
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            "load scripts": 0.23009085655212402,
            "reload script modules": 0.0627741813659668,
            "load upscalers": 0.0,
            "refresh VAE": 0.0,
            "refresh textual inversion templates": 0.0,
            "scripts list_optimizers": 0.0,
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            "reload hypernetworks": 0.0,
            "initialize extra networks": 0.0,
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    },
    "Packages": [
        "absl-py==2.0.0",
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        "ftfy==6.1.3",
        "future==0.18.3",
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        "gfpgan==1.3.8",
        "gitdb==4.0.11",
        "gitpython==3.1.32",
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        "grpcio==1.60.0",
        "h11==0.12.0",
        "httpcore==0.15.0",
        "httpx==0.24.1",
        "huggingface-hub==0.20.2",
        "idna==3.6",
        "imageio==2.33.1",
        "importlib-metadata==7.0.1",
        "importlib-resources==6.1.1",
        "inflection==0.5.1",
        "jinja2==3.1.2",
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        "jsonschema-specifications==2023.12.1",
        "jsonschema==4.20.0",
        "kiwisolver==1.4.5",
        "kornia==0.6.7",
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        "lazy-loader==0.3",
        "lightning-utilities==0.10.0",
        "llvmlite==0.41.1",
        "lmdb==1.4.1",
        "lpips==0.1.4",
        "markdown==3.5.1",
        "markupsafe==2.1.3",
        "matplotlib==3.8.2",
        "mpmath==1.3.0",
        "multidict==6.0.4",
        "networkx==3.2.1",
        "numba==0.58.1",
        "numpy==1.23.5",
        "omegaconf==2.2.3",
        "open-clip-torch==2.20.0",
        "opencv-python==4.9.0.80",
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        "piexif==1.1.3",
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        "pip==23.3.2",
        "platformdirs==4.1.0",
        "protobuf==3.20.0",
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        "pydub==0.25.1",
        "pyparsing==3.1.1",
        "pysocks==1.7.1",
        "python-dateutil==2.8.2",
        "python-multipart==0.0.6",
        "pytorch-lightning==1.9.4",
        "pytz==2023.3.post1",
        "pywavelets==1.5.0",
        "pyyaml==6.0.1",
        "realesrgan==0.3.0",
        "referencing==0.32.1",
        "regex==2023.12.25",
        "requests==2.31.0",
        "resize-right==0.0.2",
        "rpds-py==0.16.2",
        "safetensors==0.3.1",
        "scikit-image==0.21.0",
        "scipy==1.11.4",
        "semantic-version==2.10.0",
        "sentencepiece==0.1.99",
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        "six==1.16.0",
        "smmap==5.0.1",
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        "tf-keras-nightly==2.16.0.dev2024010910",
        "tifffile==2023.12.9",
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        "tokenizers==0.13.3",
        "tomesd==0.1.3",
        "tomli==2.0.1",
        "toolz==0.12.0",
        "torch==2.0.1+cu118",
        "torchdiffeq==0.2.3",
        "torchmetrics==1.2.1",
        "torchsde==0.2.6",
        "torchvision==0.15.2+cu118",
        "tqdm==4.66.1",
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        "typing-extensions==4.9.0",
        "tzdata==2023.4",
        "urllib3==2.1.0",
        "uvicorn==0.25.0",
        "wcwidth==0.2.13",
        "websockets==11.0.3",
        "werkzeug==3.0.1",
        "wheel==0.42.0",
        "yapf==0.40.2",
        "yarl==1.9.4",
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}

### Console logs

```Shell
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
Commit hash: cf2772fab0af5573da775e7437e6acdca424f26e
Launching Web UI with arguments:
no module 'xformers'. Processing without...
no module 'xformers'. Processing without...
No module 'xformers'. Proceeding without it.
Style database not found: C:\Users\user\Downloads\sd.webui\webui\styles.csv
Loading weights [41b6846108] from C:\Users\user\Downloads\sd.webui\webui\models\Stable-diffusion\cyberrealistic_v41BackToBasics.safetensors
Running on local URL:  http://127.0.0.1:7860
Creating model from config: C:\Users\user\Downloads\sd.webui\webui\configs\v1-inference.yaml

To create a public link, set `share=True` in `launch()`.
Startup time: 18.3s (prepare environment: 4.7s, import torch: 4.6s, import gradio: 2.1s, setup paths: 2.4s, initialize shared: 0.2s, other imports: 1.7s, setup codeformer: 0.2s, load scripts: 1.3s, create ui: 0.6s, gradio launch: 0.4s).
Applying attention optimization: Doggettx... done.
Model loaded in 5.6s (load weights from disk: 0.8s, create model: 0.4s, apply weights to model: 1.4s, load textual inversion embeddings: 1.8s, calculate empty prompt: 1.1s).
100%|███████████████████████████████████████████████████████████████████████████████████████████████| 16/16 [00:02<00:00,  7.71it/s]
Total progress: 100%|███████████████████████████████████████████████████████████████████████████████| 16/16 [00:01<00:00,  8.56it/s]
Total progress: 100%|███████████████████████████████████████████████████████████████████████████████| 16/16 [00:01<00:00,  8.95it/s]
```


### Additional information

_No response_