Upload app.py

app.py

@@ -2,6 +2,8 @@ import gradio as gr
 
 from annotator.util import resize_image, HWC3
 
+DESCRIPTION = '# ControlNet v1.1 (cpu_only)'
+
 
 model_canny = None
 
@@ -15,85 +17,6 @@ def canny(img, res, l, h):
     result = model_canny(img, l, h)
     return [result]
 
-
-model_hed = None
-
-
-def hed(img, res):
-    img = resize_image(HWC3(img), res)
-    global model_hed
-    if model_hed is None:
-        from annotator.hed import HEDdetector
-        model_hed = HEDdetector()
-    result = model_hed(img)
-    return [result]
-
-
-model_pidi = None
-
-
-def pidi(img, res):
-    img = resize_image(HWC3(img), res)
-    global model_pidi
-    if model_pidi is None:
-        from annotator.pidinet import PidiNetDetector
-        model_pidi = PidiNetDetector()
-    result = model_pidi(img)
-    return [result]
-
-
-model_mlsd = None
-
-
-def mlsd(img, res, thr_v, thr_d):
-    img = resize_image(HWC3(img), res)
-    global model_mlsd
-    if model_mlsd is None:
-        from annotator.mlsd import MLSDdetector
-        model_mlsd = MLSDdetector()
-    result = model_mlsd(img, thr_v, thr_d)
-    return [result]
-
-
-model_midas = None
-
-
-def midas(img, res):
-    img = resize_image(HWC3(img), res)
-    global model_midas
-    if model_midas is None:
-        from annotator.midas import MidasDetector
-        model_midas = MidasDetector()
-    result = model_midas(img)
-    return [result]
-
-
-model_zoe = None
-
-
-def zoe(img, res):
-    img = resize_image(HWC3(img), res)
-    global model_zoe
-    if model_zoe is None:
-        from annotator.zoe import ZoeDetector
-        model_zoe = ZoeDetector()
-    result = model_zoe(img)
-    return [result]
-
-
-model_normalbae = None
-
-
-def normalbae(img, res):
-    img = resize_image(HWC3(img), res)
-    global model_normalbae
-    if model_normalbae is None:
-        from annotator.normalbae import NormalBaeDetector
-        model_normalbae = NormalBaeDetector()
-    result = model_normalbae(img)
-    return [result]
-
-
 model_openpose = None
 
 
@@ -107,71 +30,6 @@ def openpose(img, res, hand_and_face):
     return [result]
 
 
-model_uniformer = None
-
-
-def uniformer(img, res):
-    img = resize_image(HWC3(img), res)
-    global model_uniformer
-    if model_uniformer is None:
-        from annotator.uniformer import UniformerDetector
-        model_uniformer = UniformerDetector()
-    result = model_uniformer(img)
-    return [result]
-
-
-model_lineart_anime = None
-
-
-def lineart_anime(img, res):
-    img = resize_image(HWC3(img), res)
-    global model_lineart_anime
-    if model_lineart_anime is None:
-        from annotator.lineart_anime import LineartAnimeDetector
-        model_lineart_anime = LineartAnimeDetector()
-    result = model_lineart_anime(img)
-    return [result]
-
-
-model_lineart = None
-
-
-def lineart(img, res, coarse=False):
-    img = resize_image(HWC3(img), res)
-    global model_lineart
-    if model_lineart is None:
-        from annotator.lineart import LineartDetector
-        model_lineart = LineartDetector()
-    result = model_lineart(img, coarse)
-    return [result]
-
-
-model_oneformer_coco = None
-
-
-def oneformer_coco(img, res):
-    img = resize_image(HWC3(img), res)
-    global model_oneformer_coco
-    if model_oneformer_coco is None:
-        from annotator.oneformer import OneformerCOCODetector
-        model_oneformer_coco = OneformerCOCODetector()
-    result = model_oneformer_coco(img)
-    return [result]
-
-
-model_oneformer_ade20k = None
-
-
-def oneformer_ade20k(img, res):
-    img = resize_image(HWC3(img), res)
-    global model_oneformer_ade20k
-    if model_oneformer_ade20k is None:
-        from annotator.oneformer import OneformerADE20kDetector
-        model_oneformer_ade20k = OneformerADE20kDetector()
-    result = model_oneformer_ade20k(img)
-    return [result]
-
-
 model_content_shuffler = None
 
 
@@ -213,75 +71,6 @@ with block:
             gallery = gr.Gallery(label="Generated images", show_label=False).style(height="auto")
     run_button.click(fn=canny, inputs=[input_image, resolution, low_threshold, high_threshold], outputs=[gallery])
 
-    with gr.Row():
-        gr.Markdown("## HED Edge")
-    with gr.Row():
-        with gr.Column():
-            input_image = gr.Image(source='upload', type="numpy")
-            resolution = gr.Slider(label="resolution", minimum=256, maximum=1024, value=512, step=64)
-            run_button = gr.Button(label="Run")
-        with gr.Column():
-            gallery = gr.Gallery(label="Generated images", show_label=False).style(height="auto")
-    run_button.click(fn=hed, inputs=[input_image, resolution], outputs=[gallery])
-
-    with gr.Row():
-        gr.Markdown("## Pidi Edge")
-    with gr.Row():
-        with gr.Column():
-            input_image = gr.Image(source='upload', type="numpy")
-            resolution = gr.Slider(label="resolution", minimum=256, maximum=1024, value=512, step=64)
-            run_button = gr.Button(label="Run")
-        with gr.Column():
-            gallery = gr.Gallery(label="Generated images", show_label=False).style(height="auto")
-    run_button.click(fn=pidi, inputs=[input_image, resolution], outputs=[gallery])
-
-    with gr.Row():
-        gr.Markdown("## MLSD Edge")
-    with gr.Row():
-        with gr.Column():
-            input_image = gr.Image(source='upload', type="numpy")
-            value_threshold = gr.Slider(label="value_threshold", minimum=0.01, maximum=2.0, value=0.1, step=0.01)
-            distance_threshold = gr.Slider(label="distance_threshold", minimum=0.01, maximum=20.0, value=0.1, step=0.01)
-            resolution = gr.Slider(label="resolution", minimum=256, maximum=1024, value=384, step=64)
-            run_button = gr.Button(label="Run")
-        with gr.Column():
-            gallery = gr.Gallery(label="Generated images", show_label=False).style(height="auto")
-    run_button.click(fn=mlsd, inputs=[input_image, resolution, value_threshold, distance_threshold], outputs=[gallery])
-
-    with gr.Row():
-        gr.Markdown("## MIDAS Depth")
-    with gr.Row():
-        with gr.Column():
-            input_image = gr.Image(source='upload', type="numpy")
-            resolution = gr.Slider(label="resolution", minimum=256, maximum=1024, value=384, step=64)
-            run_button = gr.Button(label="Run")
-        with gr.Column():
-            gallery = gr.Gallery(label="Generated images", show_label=False).style(height="auto")
-    run_button.click(fn=midas, inputs=[input_image, resolution], outputs=[gallery])
-
-
-    with gr.Row():
-        gr.Markdown("## Zoe Depth")
-    with gr.Row():
-        with gr.Column():
-            input_image = gr.Image(source='upload', type="numpy")
-            resolution = gr.Slider(label="resolution", minimum=256, maximum=1024, value=512, step=64)
-            run_button = gr.Button(label="Run")
-        with gr.Column():
-            gallery = gr.Gallery(label="Generated images", show_label=False).style(height="auto")
-    run_button.click(fn=zoe, inputs=[input_image, resolution], outputs=[gallery])
-
-    with gr.Row():
-        gr.Markdown("## Normal Bae")
-    with gr.Row():
-        with gr.Column():
-            input_image = gr.Image(source='upload', type="numpy")
-            resolution = gr.Slider(label="resolution", minimum=256, maximum=1024, value=512, step=64)
-            run_button = gr.Button(label="Run")
-        with gr.Column():
-            gallery = gr.Gallery(label="Generated images", show_label=False).style(height="auto")
-    run_button.click(fn=normalbae, inputs=[input_image, resolution], outputs=[gallery])
-
     with gr.Row():
         gr.Markdown("## Openpose")
     with gr.Row():
@@ -294,62 +83,6 @@ with block:
             gallery = gr.Gallery(label="Generated images", show_label=False).style(height="auto")
     run_button.click(fn=openpose, inputs=[input_image, resolution, hand_and_face], outputs=[gallery])
 
-    with gr.Row():
-        gr.Markdown("## Lineart Anime")
-    with gr.Row():
-        with gr.Column():
-            input_image = gr.Image(source='upload', type="numpy")
-            resolution = gr.Slider(label="resolution", minimum=256, maximum=1024, value=512, step=64)
-            run_button = gr.Button(label="Run")
-        with gr.Column():
-            gallery = gr.Gallery(label="Generated images", show_label=False).style(height="auto")
-    run_button.click(fn=lineart_anime, inputs=[input_image, resolution], outputs=[gallery])
-
-    with gr.Row():
-        gr.Markdown("## Lineart")
-    with gr.Row():
-        with gr.Column():
-            input_image = gr.Image(source='upload', type="numpy")
-            coarse = gr.Checkbox(label='Using coarse model', value=False)
-            resolution = gr.Slider(label="resolution", minimum=256, maximum=1024, value=512, step=64)
-            run_button = gr.Button(label="Run")
-        with gr.Column():
-            gallery = gr.Gallery(label="Generated images", show_label=False).style(height="auto")
-    run_button.click(fn=lineart, inputs=[input_image, resolution, coarse], outputs=[gallery])
-
-    with gr.Row():
-        gr.Markdown("## Uniformer Segmentation")
-    with gr.Row():
-        with gr.Column():
-            input_image = gr.Image(source='upload', type="numpy")
-            resolution = gr.Slider(label="resolution", minimum=256, maximum=1024, value=512, step=64)
-            run_button = gr.Button(label="Run")
-        with gr.Column():
-            gallery = gr.Gallery(label="Generated images", show_label=False).style(height="auto")
-    run_button.click(fn=uniformer, inputs=[input_image, resolution], outputs=[gallery])
-
-    with gr.Row():
-        gr.Markdown("## Oneformer COCO Segmentation")
-    with gr.Row():
-        with gr.Column():
-            input_image = gr.Image(source='upload', type="numpy")
-            resolution = gr.Slider(label="resolution", minimum=256, maximum=1024, value=512, step=64)
-            run_button = gr.Button(label="Run")
-        with gr.Column():
-            gallery = gr.Gallery(label="Generated images", show_label=False).style(height="auto")
-    run_button.click(fn=oneformer_coco, inputs=[input_image, resolution], outputs=[gallery])
-
-    with gr.Row():
-        gr.Markdown("## Oneformer ADE20K Segmentation")
-    with gr.Row():
-        with gr.Column():
-            input_image = gr.Image(source='upload', type="numpy")
-            resolution = gr.Slider(label="resolution", minimum=256, maximum=1024, value=640, step=64)
-            run_button = gr.Button(label="Run")
-        with gr.Column():
-            gallery = gr.Gallery(label="Generated images", show_label=False).style(height="auto")
-    run_button.click(fn=oneformer_ade20k, inputs=[input_image, resolution], outputs=[gallery])
-
     with gr.Row():
         gr.Markdown("## Content Shuffle")
     with gr.Row():