Upload app.py

app.py

@@ -31,7 +31,6 @@ PARAMS = {
     "points_per_batch":       32,
     "min_mask_region_area":   4500,
     "box_nms_thresh":         0.8,
-    "crops_n_layers":         1,
 }
 
 
@@ -68,7 +67,6 @@ def segmentar(
     points_per_batch: int,
     min_mask_region_area: int,
     box_nms_thresh: float,
-    crops_n_layers: int,
 ):
     global PARAMS
     if imagen is None:
@@ -81,7 +79,6 @@ def segmentar(
         "points_per_batch":       int(points_per_batch),
         "min_mask_region_area":   int(min_mask_region_area),
         "box_nms_thresh":         float(box_nms_thresh),
-        "crops_n_layers":         int(crops_n_layers),
     })
 
     _load_pipeline()
@@ -93,7 +90,6 @@ def segmentar(
         stability_score_thresh=PARAMS["stability_score_thresh"],
         min_mask_region_area=PARAMS["min_mask_region_area"],
         box_nms_thresh=PARAMS["box_nms_thresh"],
-        crops_n_layers=PARAMS["crops_n_layers"],
     )
     if isinstance(resultado, list):
         resultado = resultado[0]
@@ -105,7 +101,7 @@ def segmentar(
     info = (
         f"UI: {len(masks)} zonas  |  "
         f"iou={PARAMS['pred_iou_thresh']}  stab={PARAMS['stability_score_thresh']}  "
-        f"crops={PARAMS['crops_n_layers']}  min_area={PARAMS['min_mask_region_area']}  "
+        f"min_area={PARAMS['min_mask_region_area']}  "
         f"nms={PARAMS['box_nms_thresh']}  batch={PARAMS['points_per_batch']}"
     )
     return _render_masks(imagen_rgb, masks), info
@@ -137,7 +133,6 @@ def segment_for_backend(image_np: np.ndarray):
             stability_score_thresh=PARAMS["stability_score_thresh"],
             min_mask_region_area=PARAMS["min_mask_region_area"],
             box_nms_thresh=PARAMS["box_nms_thresh"],
-            crops_n_layers=PARAMS["crops_n_layers"],
         )
         if isinstance(resultado, list):
             resultado = resultado[0]
@@ -229,12 +224,8 @@ with gr.Blocks(title="SAM Auto - Segmentacion") as demo:
                 minimum=0.0, maximum=1.0, step=0.05, value=PARAMS["box_nms_thresh"],
                 label="box_nms_thresh  (↑ permite mas solapamiento entre mascaras)"
             )
-            sl_crops = gr.Slider(
-                minimum=0, maximum=2, step=1, value=PARAMS["crops_n_layers"],
-                label="crops_n_layers  (0=imagen completa · 1=+4 recortes · 2=+16 recortes, lento)"
-            )
 
-    all_inputs = [imagen_entrada, sl_pred_iou, sl_stability, sl_batch, sl_min_area, sl_nms, sl_crops]
+    all_inputs = [imagen_entrada, sl_pred_iou, sl_stability, sl_batch, sl_min_area, sl_nms]
     boton.click(fn=segmentar, inputs=all_inputs, outputs=[imagen_salida, estado])
     imagen_entrada.upload(fn=segmentar, inputs=all_inputs, outputs=[imagen_salida, estado])