Spaces:
Running
Running
israelweiss
commited on
Commit
•
c52d0f0
1
Parent(s):
1ae4124
redundant button, effort for faster response
Browse files
app.py
CHANGED
@@ -22,17 +22,14 @@ def download_image(url):
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response = requests.get(url)
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return Image.open(BytesIO(response.content)).convert("RGB")
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def eraser_api_call(image_base64_file, mask_base64_file,
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url = "http://engine.prod.bria-api.com/v1/eraser"
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payload = {
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"file": image_base64_file,
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"mask_file": mask_base64_file,
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"seed": seed,
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"mask_type": mask_type,
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"original_quality": original_quality,
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"text_guidance_scale": guidance_scale
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}
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response = requests.post(url, json=payload, headers=auth_headers)
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response = response.json()
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@@ -97,7 +94,7 @@ def read_content(file_path: str) -> str:
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return content
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def predict(dict
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init_image = Image.fromarray(dict['background'][:, :, :3], 'RGB') #dict['background'].convert("RGB")#.resize((1024, 1024))
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mask = Image.fromarray(dict['layers'][0][:,:,3], 'L') #dict['layers'].convert("RGB")#.resize((1024, 1024))
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@@ -106,8 +103,7 @@ def predict(dict, guidance_scale=1.2, seed=123456):
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mask_base64_file = convert_mask_image_to_base64_string(mask)
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mask_type = "manual"
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gen_img = eraser_api_call(image_base64_file, mask_base64_file, seed, mask_type, original_quality, guidance_scale)
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return gen_img
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@@ -155,9 +151,8 @@ with image_blocks as demo:
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gr.Markdown("## BRIA Eraser")
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gr.HTML('''
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<p style="margin-bottom: 10px; font-size: 94%">
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This is a demo for
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BRIA Eraser enables the ability to clear out and clean areas in an image or remove specific elements, while trained on licensed data, and so provide full legal liability coverage for copyright and privacy infringement.
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</p>
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''')
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with gr.Row():
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@@ -165,17 +160,12 @@ with image_blocks as demo:
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image = gr.ImageEditor(sources=["upload"], layers=False, transforms=[], brush=gr.Brush(colors=["#000000"], color_mode="fixed"))
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with gr.Row(elem_id="prompt-container", equal_height=True):
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btn = gr.Button("Inpaint!", elem_id="run_button")
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with gr.Accordion(label="Advanced Settings", open=False):
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with gr.Row(equal_height=True):
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guidance_scale = gr.Number(value=1.2, minimum=0.0, maximum=2.5, step=0.1, label="guidance_scale")
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seed = gr.Number(value=123456, minimum=0, maximum=999999, step=1, label="seed")
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with gr.Column():
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image_out = gr.Image(label="Output", elem_id="output-img", height=400)
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# Button click will trigger the inpainting function (no prompt required)
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btn.click(fn=predict, inputs=[image
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gr.HTML(
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@@ -187,4 +177,5 @@ with image_blocks as demo:
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"""
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)
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image_blocks.queue(max_size=25,api_open=False).launch(show_api=False)
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response = requests.get(url)
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return Image.open(BytesIO(response.content)).convert("RGB")
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def eraser_api_call(image_base64_file, mask_base64_file, mask_type):
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url = "http://engine.prod.bria-api.com/v1/eraser"
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payload = {
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"file": image_base64_file,
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"mask_file": mask_base64_file,
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"mask_type": mask_type,
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}
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response = requests.post(url, json=payload, headers=auth_headers)
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response = response.json()
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return content
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def predict(dict):
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init_image = Image.fromarray(dict['background'][:, :, :3], 'RGB') #dict['background'].convert("RGB")#.resize((1024, 1024))
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mask = Image.fromarray(dict['layers'][0][:,:,3], 'L') #dict['layers'].convert("RGB")#.resize((1024, 1024))
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mask_base64_file = convert_mask_image_to_base64_string(mask)
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mask_type = "manual"
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gen_img = eraser_api_call(image_base64_file, mask_base64_file, mask_type)
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return gen_img
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gr.Markdown("## BRIA Eraser")
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gr.HTML('''
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<p style="margin-bottom: 10px; font-size: 94%">
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This is a demo for BRIA Eraser which enables the ability to remove specific elements or objects.
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The model was trained on licensed data, and so provide full legal liability coverage for copyright and privacy infringement.
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</p>
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''')
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with gr.Row():
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image = gr.ImageEditor(sources=["upload"], layers=False, transforms=[], brush=gr.Brush(colors=["#000000"], color_mode="fixed"))
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with gr.Row(elem_id="prompt-container", equal_height=True):
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btn = gr.Button("Inpaint!", elem_id="run_button")
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with gr.Column():
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image_out = gr.Image(label="Output", elem_id="output-img", height=400)
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# Button click will trigger the inpainting function (no prompt required)
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btn.click(fn=predict, inputs=[image], outputs=[image_out], api_name='run')
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gr.HTML(
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"""
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)
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# image_blocks.queue(max_size=25,api_open=False).launch(show_api=False)
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demo.launch()
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