add deprecated gradio class

README.md

@@ -6,7 +6,7 @@ colorTo: "indigo"           # The ending color of the gradient in your Space thu
 sdk: "gradio"               # The SDK you're using (gradio/streamlit/docker/static)
 sdk_version: "2.8.9"        # The version of the SDK
 app_file: "app.py"          # The file that contains your app. Make sure the path is correct.
-python_version: "3.11"       # Specify the python version, default is 3.10
+python_version: "3.11.9"       # Specify the python version, default is 3.10
 pinned: false               # Whether your Space stays pinned on your profile
 lisence: mit
 ---

app.py

@@ -14,6 +14,7 @@ from plots import get_pre_define_colors
 from utils.load_model import load_xclip
 from utils.predict import xclip_pred
 
+from utils.old_gradio_class import SelectData
 
 DEVICE = "cpu"
 XCLIP, OWLVIT_PRECESSOR = load_xclip(DEVICE)
@@ -21,7 +22,7 @@ XCLIP_DESC_PATH = "data/jsons/bs_cub_desc.json"
 XCLIP_DESC = json.load(open(XCLIP_DESC_PATH, "r"))
 PREPROCESS = lambda x: OWLVIT_PRECESSOR(images=x, return_tensors='pt')
 IMAGES_FOLDER = "data/images"
-# XCLIP_RESULTS = json.load(open("data/jsons/xclip_org.json", "r"))
+XCLIP_RESULTS = json.load(open("data/jsons/xclip_org.json", "r"))
 # correct_predictions = [k for k, v in XCLIP_RESULTS.items() if v['prediction']]
 
 # get the intersection of sachit and xclip (revised)
@@ -206,7 +207,7 @@ blank_image = np.array(Image.open('data/images/final.png').convert('RGB'))
 PART_IMAGES_DICT = {file_name: load_part_images(file_name) for file_name in IMAGE_FILE_LIST}
 
 # --- Gradio Functions ---
-def update_selected_image(event: gr.SelectData):
+def update_selected_image(event: SelectData):
     image_height = 400
     index = event.index
 

utils/old_gradio_class.py

@@ -0,0 +1,19 @@
+from gradio.helpers import EventData
+from gradio.blocks import Block
+from typing import Any
+
+class SelectData(EventData):
+    def __init__(self, target: Block | None, data: Any):
+        super().__init__(target, data)
+        self.index: int | tuple[int, int] = data["index"]
+        """
+        The index of the selected item. Is a tuple if the component is two dimensional or selection is a range.
+        """
+        self.value: Any = data["value"]
+        """
+        The value of the selected item.
+        """
+        self.selected: bool = data.get("selected", True)
+        """
+        True if the item was selected, False if deselected.
+        """