refactor(model_loader): update dataset names for model registrations in the loader

refactor(ui): change confidence slider default value and update predictions dataframe headers

app.py

@@ -428,7 +428,7 @@ with gr.Blocks() as detection_model_eval_playground:
     with gr.Row():
         with gr.Column():
             img_input = gr.Image(label="Upload Image to Analyze", sources=['upload', 'webcam'], type='filepath')
-            confidence_slider = gr.Slider(0.0, 1.0, value=0.7, step=0.05, label="Confidence Threshold")
+            confidence_slider = gr.Slider(0.0, 1.0, value=0.8, step=0.05, label="Confidence Threshold", visible=False)
             rotate_slider = gr.Slider(0, 45, value=0, step=1, label="Rotate Degrees", visible=False)
             noise_slider = gr.Slider(0, 50, value=0, step=1, label="Noise Level", visible=False)
             sharpen_slider = gr.Slider(0, 50, value=0, step=1, label="Sharpen Strength", visible=False)
@@ -438,7 +438,7 @@ with gr.Blocks() as detection_model_eval_playground:
 
             predictions_df = gr.Dataframe(
                 label="Model Predictions",
-                headers=["Arch / Dataset", "By", "AI", "Real", "Label"],
+                headers=["Model", "By", "AI", "Real", "Label"],
                 datatype=["str", "str", "number", "number", "str"],
                 show_label=False,
                 row_count=(8, "dynamic")

utils/model_loader.py

@@ -86,11 +86,11 @@ def register_all_models(MODEL_PATHS, CLASS_NAMES, device, infer_onnx_model, prep
             if model_key == "model_1":
                 contributor = "haywoodsloan"
                 architecture = "SwinV2"
-                dataset = "DeepFakeDetection"
+                dataset = "Mixed"
             elif model_key == "model_2":
                 contributor = "Heem2"
                 architecture = "ViT"
-                dataset = "DeepFakeDetection"
+                dataset = "Mixed"
             elif model_key == "model_3":
                 contributor = "Organika"
                 architecture = "VIT"
@@ -126,7 +126,7 @@ def register_all_models(MODEL_PATHS, CLASS_NAMES, device, infer_onnx_model, prep
         elif model_key == "model_8":
             contributor = "aiwithoutborders-xyz"
             architecture = "ViT"
-            dataset = "DeepfakeDetection"
+            dataset = "Massive"
             display_name_parts = [model_num]
             if architecture and architecture not in ["Unknown"]:
                 display_name_parts.append(architecture)