remove redundant code

app.py

@@ -6,9 +6,7 @@ import random
 from utils import image_comparison
 from utils import sahi_mmdet_inference
 
-MMDET_YOLACT_MODEL_URL = "https://download.openmmlab.com/mmdetection/v2.0/yolact/yolact_r50_1x8_coco/yolact_r50_1x8_coco_20200908-f38d58df.pth"
 MMDET_YOLOX_MODEL_URL = "https://download.openmmlab.com/mmdetection/v2.0/yolox/yolox_tiny_8x8_300e_coco/yolox_tiny_8x8_300e_coco_20210806_234250-4ff3b67e.pth"
-MMDET_FASTERRCNN_MODEL_URL = "https://download.openmmlab.com/mmdetection/v2.0/faster_rcnn/faster_rcnn_r50_fpn_2x_coco/faster_rcnn_r50_fpn_2x_coco_bbox_mAP-0.384_20200504_210434-a5d8aa15.pth"
 
 IMAGE_TO_URL = {
     "apple_tree.jpg": "https://user-images.githubusercontent.com/34196005/142730935-2ace3999-a47b-49bb-83e0-2bdd509f1c90.jpg",
@@ -21,34 +19,15 @@ IMAGE_TO_URL = {
 
 
 @st.cache(allow_output_mutation=True, show_spinner=False)
-def get_mmdet_model(model_name: str):
-    if model_name == "yolact":
-        model_path = "yolact.pt"
-        sahi.utils.file.download_from_url(
-            MMDET_YOLACT_MODEL_URL,
-            model_path,
-        )
-        config_path = sahi.utils.mmdet.download_mmdet_config(
-            model_name="yolact", config_file_name="yolact_r50_1x8_coco.py"
-        )
-    elif model_name == "yolox":
-        model_path = "yolox.pt"
-        sahi.utils.file.download_from_url(
-            MMDET_YOLOX_MODEL_URL,
-            model_path,
-        )
-        config_path = sahi.utils.mmdet.download_mmdet_config(
-            model_name="yolox", config_file_name="yolox_tiny_8x8_300e_coco.py"
-        )
-    elif model_name == "faster_rcnn":
-        model_path = "faster_rcnn.pt"
-        sahi.utils.file.download_from_url(
-            MMDET_FASTERRCNN_MODEL_URL,
-            model_path,
-        )
-        config_path = sahi.utils.mmdet.download_mmdet_config(
-            model_name="faster_rcnn", config_file_name="faster_rcnn_r50_fpn_2x_coco.py"
-        )
+def get_model(model_name: str):
+    model_path = "yolox.pt"
+    sahi.utils.file.download_from_url(
+        MMDET_YOLOX_MODEL_URL,
+        model_path,
+    )
+    config_path = sahi.utils.mmdet.download_mmdet_config(
+        model_name="yolox", config_file_name="yolox_tiny_8x8_300e_coco.py"
+    )
 
     detection_model = sahi.model.MmdetDetectionModel(
         model_path=model_path,
@@ -183,7 +162,6 @@ with col1:
 with col3:
     st.markdown(f"##### Set SAHI parameters:")
 
-    model_name = "yolox"
     slice_size = st.number_input("slice_size", min_value=256, value=512, step=256)
     overlap_ratio = st.number_input(
         "overlap_ratio", min_value=0.0, max_value=0.6, value=0.2, step=0.2
@@ -209,12 +187,9 @@ if submit:
         text="Downloading model weight.. "
         + st.session_state["last_spinner_texts"].get()
     ):
-        detection_model = get_mmdet_model(model_name)
+        detection_model = get_model()
 
-    if model_name == "yolox":
-        image_size = 416
-    else:
-        image_size = 640
+    image_size = 416
 
     with st.spinner(
         text="Performing prediction.. " + st.session_state["last_spinner_texts"].get()