v2 version

app.py

@@ -44,14 +44,21 @@ def load_models():
                                                     'yolov8x_person_face.pt',
                                                     use_auth_token=HF_TOKEN)
 
-    age_gender_path = huggingface_hub.hf_hub_download('iitolstykh/demo_xnet_volo_cross',
+    age_gender_path_v1 = huggingface_hub.hf_hub_download('iitolstykh/demo_xnet_volo_cross',
                                                       'checkpoint-377.pth.tar',
                                                       use_auth_token=HF_TOKEN)
 
-    predictor_cfg = Cfg(detector_path, age_gender_path)
-    predictor = Predictor(predictor_cfg)
+    age_gender_path_v2 = huggingface_hub.hf_hub_download('iitolstykh/demo_xnet_volo_cross',
+                                                         'mivolo_v2_1.tar',
+                                                         use_auth_token=HF_TOKEN)
 
-    return predictor
+    predictor_cfg_v1 = Cfg(detector_path, age_gender_path_v1)
+    predictor_cfg_v2 = Cfg(detector_path, age_gender_path_v2)
+
+    predictor_v1 = Predictor(predictor_cfg_v1)
+    predictor_v2 = Predictor(predictor_cfg_v2)
+
+    return predictor_v1, predictor_v2
 
 
 def detect(
@@ -88,18 +95,42 @@ def clear():
     return None, 0.4, 0.7, "Use persons and faces", None
 
 
-predictor = load_models()
+predictor_v1, predictor_v2 = load_models()
+prediction_func_v1 = functools.partial(detect, predictor=predictor_v1)
+prediction_func_v2 = functools.partial(detect, predictor=predictor_v2)
 
 image_dir = pathlib.Path('images')
 examples = [[path.as_posix(), 0.4, 0.7, "Use persons and faces"] for path in sorted(image_dir.glob('*.jpg'))]
 
-func = functools.partial(detect, predictor=predictor)
+with gr.Blocks(theme=gr.themes.Default(), css="style.css") as demo_v1:
+    with gr.Row():
+        with gr.Column():
+            image = gr.Image(label='Input', type='numpy')
+            score_threshold = gr.Slider(0, 1, value=0.4, step=0.05, label='Detector Score Threshold')
+            iou_threshold = gr.Slider(0, 1, value=0.7, step=0.05, label='NMS Iou Threshold')
+            mode = gr.Radio(["Use persons and faces", "Use persons only", "Use faces only"],
+                            value="Use persons and faces",
+                            label="Inference mode",
+                            info="What to use for gender and age recognition")
 
-with gr.Blocks(
-    theme=gr.themes.Default(),
-    css="style.css"
-) as demo:
-    gr.Markdown(DESCRIPTION)
+            with gr.Row():
+                clear_button = gr.Button("Clear")
+                with gr.Column():
+                    run_button = gr.Button("Submit", variant="primary")
+        with gr.Column():
+            result = gr.Image(label='Output', type='numpy')
+
+    inputs = [image, score_threshold, iou_threshold, mode]
+    gr.Examples(examples=examples,
+                inputs=inputs,
+                outputs=result,
+                fn=prediction_func_v1,
+                cache_examples=False)
+    run_button.click(fn=prediction_func_v1, inputs=inputs, outputs=result, api_name='predict')
+    clear_button.click(fn=clear, inputs=None, outputs=[image, score_threshold, iou_threshold, mode, result])
+
+
+with gr.Blocks(theme=gr.themes.Default(), css="style.css") as demo_v2:
     with gr.Row():
         with gr.Column():
             image = gr.Image(label='Input', type='numpy')
@@ -121,9 +152,21 @@ with gr.Blocks(
     gr.Examples(examples=examples,
                 inputs=inputs,
                 outputs=result,
-                fn=func,
+                fn=prediction_func_v2,
                 cache_examples=False)
-    run_button.click(fn=func, inputs=inputs, outputs=result, api_name='predict')
+    run_button.click(fn=prediction_func_v2, inputs=inputs, outputs=result, api_name='predict')
     clear_button.click(fn=clear, inputs=None, outputs=[image, score_threshold, iou_threshold, mode, result])
 
-demo.queue(max_size=15).launch()
+
+with gr.Blocks(theme=gr.themes.Default(), css="style.css") as demo:
+    gr.Markdown(DESCRIPTION)
+
+    with gr.Tabs():
+        with gr.Tab(label="MiVOLO_V1"):
+            demo_v1.render()
+        with gr.Tab(label="MiVOLO_V2"):
+            demo_v2.render()
+
+
+if __name__ == "__main__":
+    demo.queue(max_size=15).launch()

requirements.txt

@@ -1,5 +1,5 @@
 Cython==0.29.28
-ultralytics
+ultralytics==8.0.124
 timm==0.8.13.dev0
 huggingface_hub
 gradio