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Merge pull request #1138 from ZeroCool940711/dev
Small fix to the custom model list.
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commit
178e62292e
@ -599,14 +599,14 @@ def layout():
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# If we have custom models available on the "models/custom"
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#folder then we show a menu to select which model we want to use, otherwise we use the main model for SD
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if st.session_state["CustomModel_available"]:
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custom_model = st.selectbox("Custom Model:", st.session_state["custom_models"],
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index=st.session_state["custom_models"].index(st.session_state["defaults"].general.default_model),
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custom_model = st.selectbox("Custom Model:", st.session_state["defaults"].txt2vid.custom_models_list,
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index=st.session_state["defaults"].txt2vid.custom_models_list.index(st.session_state["defaults"].txt2vid.default_model),
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help="Select the model you want to use. This option is only available if you have custom models \
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on your 'models/custom' folder. The model name that will be shown here is the same as the name\
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the file for the model has on said folder, it is recommended to give the .ckpt file a name that \
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will make it easier for you to distinguish it from other models. Default: Stable Diffusion v1.4")
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else:
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custom_model = "Stable Diffusion v1.4"
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custom_model = "CompVis/stable-diffusion-v1-4"
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#st.session_state["weights_path"] = custom_model
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#else:
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@ -676,10 +676,10 @@ def layout():
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if generate_button:
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#print("Loading models")
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# load the models when we hit the generate button for the first time, it wont be loaded after that so dont worry.
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load_models(False, False, False, RealESRGAN_model, CustomModel_available=CustomModel_available, custom_model=custom_model)
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#load_models(False, False, False, st.session_state["RealESRGAN_model"], CustomModel_available=st.session_state["CustomModel_available"], custom_model=custom_model)
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# run video generation
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image, seed, info, stats = txt2vid(prompts=prompt, gpu=st.session_state['defaults'].general.gpu,
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image, seed, info, stats = txt2vid(prompts=prompt, gpu=st.session_state["defaults"].general.gpu,
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num_steps=st.session_state.sampling_steps, max_frames=int(st.session_state.max_frames),
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num_inference_steps=st.session_state.num_inference_steps,
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cfg_scale=cfg_scale,do_loop=st.session_state["do_loop"],
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