Spaces:
Running
on
A10G
Running
on
A10G
BertChristiaens
commited on
Commit
•
b999def
1
Parent(s):
c882d5b
bugfix
Browse files
app.py
CHANGED
@@ -93,7 +93,7 @@ def make_prompt_row():
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with col_0_0:
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st.text_input(label="Positive prompt", value="a photograph of a room, interior design, 4k, high resolution", key='positive_prompt')
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with col_0_1:
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-
st.text_input(label="Negative prompt", value="", key='negative_prompt')
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def make_sidebar():
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with st.sidebar:
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@@ -255,7 +255,7 @@ def make_editing_canvas(canvas_color, brush, _reset_state, generation_mode, pain
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image=Image.fromarray(image),
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mask_image=mask,
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negative_prompt=st.session_state['negative_prompt'],
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-
)
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if isinstance(result_image, np.ndarray):
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result_image = Image.fromarray(result_image)
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st.session_state['output_image'] = result_image
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with col_0_0:
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st.text_input(label="Positive prompt", value="a photograph of a room, interior design, 4k, high resolution", key='positive_prompt')
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with col_0_1:
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+
st.text_input(label="Negative prompt", value="low res, blur, ", key='negative_prompt')
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def make_sidebar():
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with st.sidebar:
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image=Image.fromarray(image),
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mask_image=mask,
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negative_prompt=st.session_state['negative_prompt'],
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+
)
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if isinstance(result_image, np.ndarray):
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result_image = Image.fromarray(result_image)
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st.session_state['output_image'] = result_image
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models.py
CHANGED
@@ -52,7 +52,7 @@ def make_image_controlnet(image: np.ndarray,
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generated_image = pipe(
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prompt=positive_prompt,
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negative_prompt=negative_prompt,
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-
num_inference_steps=
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strength=1.00,
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guidance_scale=7.0,
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generator=[torch.Generator(device="cuda").manual_seed(seed)],
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@@ -89,7 +89,7 @@ def make_inpainting(positive_prompt: str,
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mask_image=mask_image,
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prompt=positive_prompt,
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negative_prompt=negative_prompt,
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-
num_inference_steps=
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height=HEIGHT,
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width=WIDTH,
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).images[0]
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generated_image = pipe(
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prompt=positive_prompt,
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negative_prompt=negative_prompt,
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+
num_inference_steps=30,
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strength=1.00,
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guidance_scale=7.0,
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generator=[torch.Generator(device="cuda").manual_seed(seed)],
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mask_image=mask_image,
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prompt=positive_prompt,
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negative_prompt=negative_prompt,
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+
num_inference_steps=30,
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height=HEIGHT,
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width=WIDTH,
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).images[0]
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