remove hardcoding

app.py

@@ -47,7 +47,7 @@ import numpy as np
 from PIL import Image
 
 @weave.op()
-def detect_brain_tumor_owlv2(image, seg_input, debug: bool = True):
+def detect_object_owlv2(image, seg_input, debug: bool = True):
     """
     Detects a brain tumor in the given image and returns the annotated image.
 
@@ -61,7 +61,7 @@ def detect_brain_tumor_owlv2(image, seg_input, debug: bool = True):
     """
 
     # Step 2: Detect brain tumor using owl_v2
-    prompt = "detect brain tumor"
+    prompt = seg_input
     detections = owl_v2(prompt, image)
 
     # Step 3: Overlay bounding boxes on the image
@@ -86,7 +86,7 @@ def detect_brain_tumor_owlv2(image, seg_input, debug: bool = True):
     return (image_with_bboxes, annotations)
 
 @weave.op()
-def detect_brain_tumor_dino(image, seg_input, debug: bool = True):
+def detect_object_dino(image, seg_input, debug: bool = True):
     """
     Detects a brain tumor in the given image and returns the annotated image.
 
@@ -100,7 +100,7 @@ def detect_brain_tumor_dino(image, seg_input, debug: bool = True):
     """
 
     # Step 2: Detect brain tumor using grounding_dino
-    prompt = "detect brain tumor"
+    prompt = seg_input
     detections = grounding_dino(prompt, image)
 
     # Step 3: Overlay bounding boxes on the image
@@ -125,7 +125,7 @@ def detect_brain_tumor_dino(image, seg_input, debug: bool = True):
     return (image_with_bboxes, annotations)
 
 @weave.op()
-def detect_brain_tumor_florence2(image, seg_input, debug: bool = True):
+def detect_object_florence2(image, seg_input, debug: bool = True):
     """
     Detects a brain tumor in the given image and returns the annotated image.