add annotator

app.py

@@ -1,17 +1,12 @@
 import importlib
 import os
+
 import gradio as gr
+from omegaconf import OmegaConf
 
 from annotator.util import resize_image, HWC3
 
-config = {
-    "canny": "CannyDetector",
-    "hed": "HedDetector",
-    "mlsd": "MLSDProcessor",
-    "midas": "MidasProcessor",
-    "openpose": "OpenposeDetector",
-    "uniformer": "UniformerDetector"
-}
+config = OmegaConf.load("config/annotator.yaml")
 
 package_annotator = "annotator"
 
@@ -38,92 +33,28 @@ def process(cls):
 block = gr.Blocks().queue()
 examples = [os.path.join(os.path.dirname(__file__), "examples/demo.jpeg")]
 with block:
-    with gr.Tab("Canny Edge"):
-        with gr.Row():
-            gr.Markdown("## Canny Edge")
-        with gr.Row():
-            with gr.Column():
-                input_image = gr.Image(source='upload', type="numpy")
-                low_threshold = gr.Slider(label="low_threshold", minimum=1, maximum=255, value=100, step=1)
-                high_threshold = gr.Slider(label="high_threshold", minimum=1, maximum=255, value=200, step=1)
-                resolution = gr.Slider(label="resolution", minimum=256, maximum=1024, value=512, step=64)
-                run_button = gr.Button(label="Run")
-                gr.Examples(examples, input_image)
-            with gr.Column():
-                gallery = gr.Gallery(label="Generated images", show_label=False).style(height="auto")
-        run_button.click(fn=process(config["canny"]), inputs=[input_image, resolution, low_threshold, high_threshold],
-                         outputs=[gallery])
-
-    with gr.Tab("HED Edge"):
-        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")
-                gr.Examples(examples, input_image)
-            with gr.Column():
-                gallery = gr.Gallery(label="Generated images", show_label=False).style(height="auto")
-        run_button.click(fn=process(config["hed"]), inputs=[input_image, resolution], outputs=[gallery])
-
-    with gr.Tab("MLSD Edge"):
-        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")
-                gr.Examples(examples, input_image)
-            with gr.Column():
-                gallery = gr.Gallery(label="Generated images", show_label=False).style(height="auto")
-        run_button.click(fn=process(config["mlsd"]),
-                         inputs=[input_image, resolution, value_threshold, distance_threshold],
-                         outputs=[gallery])
-
-    with gr.Tab("MIDAS Depth and Normal"):
-        with gr.Row():
-            gr.Markdown("## MIDAS Depth and Normal")
-        with gr.Row():
-            with gr.Column():
-                input_image = gr.Image(source='upload', type="numpy")
-                alpha = gr.Slider(label="alpha", minimum=0.1, maximum=20.0, value=6.2, step=0.01)
-                resolution = gr.Slider(label="resolution", minimum=256, maximum=1024, value=384, step=64)
-                run_button = gr.Button(label="Run")
-                gr.Examples(examples, input_image)
-            with gr.Column():
-                gallery = gr.Gallery(label="Generated images", show_label=False).style(height="auto")
-        run_button.click(fn=process(config["midas"]), inputs=[input_image, resolution, alpha], outputs=[gallery])
-
-    with gr.Tab("Openpose"):
-        with gr.Row():
-            gr.Markdown("## Openpose")
-        with gr.Row():
-            with gr.Column():
-                input_image = gr.Image(source='upload', type="numpy")
-                hand = gr.Checkbox(label='detect hand', value=False)
-                resolution = gr.Slider(label="resolution", minimum=256, maximum=1024, value=512, step=64)
-                run_button = gr.Button(label="Run")
-                gr.Examples(examples, input_image)
-            with gr.Column():
-                gallery = gr.Gallery(label="Generated images", show_label=False).style(height="auto")
-        run_button.click(fn=process(config["openpose"]), inputs=[input_image, resolution, hand], outputs=[gallery])
-
-    with gr.Tab("Uniformer Segmentation"):
-        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")
-                gr.Examples(examples, input_image)
-            with gr.Column():
-                gallery = gr.Gallery(label="Generated images", show_label=False).style(height="auto")
-        run_button.click(fn=process(config["uniformer"]), inputs=[input_image, resolution], outputs=[gallery])
+    for key in config.keys():
+        cls, input_element = config[key]["process"], config[key].get("input")
+        input_append = []
+        with gr.Tab(key):
+            with gr.Row():
+                gr.Markdown("## " + key)
+            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)
+
+                    if input_element is not None:
+                        for item in input_element:
+                            input_append.append(getattr(gr, item["attr"])(**item["args"]))
+
+                    run_button = gr.Button(label="Run")
+                    gr.Examples(examples, input_image)
+                with gr.Column():
+                    gallery = gr.Gallery(label="Generated images", show_label=False).style(height="auto")
+
+            run_button.click(fn=process(cls),
+                             inputs=[input_image, resolution] + input_append,
+                             outputs=[gallery])
 
 block.launch()