added object detection to the space UI

app.py

@@ -6,7 +6,7 @@ import scipy
 from PIL import Image
 import torch.nn as nn
 from transformers import Blip2Processor, Blip2ForConditionalGeneration, InstructBlipProcessor, InstructBlipForConditionalGeneration
-from My_Model.object_detection import ObjectDetector
+from my_model.object_detection import ObjectDetector
 
 def load_caption_model(blip2=False, instructblip=True):
 
@@ -65,3 +65,56 @@ if st.button("Get Answer"):
         st.write(answer)
     else:
         st.write("Please upload an image and enter a question.")
+
+
+
+
+
+
+# Object Detection
+
+# Object Detection UI in the sidebar
+st.sidebar.title("Object Detection")
+# Dropdown to select the model
+detect_model = st.sidebar.selectbox("Choose a model for object detection:", ["detic", "yolov5"])
+# Slider for threshold with default values based on the model
+threshold = st.sidebar.slider("Select Detection Threshold", 0.1, 0.9, 0.2 if detect_model == "yolov5" else 0.4)
+# Button to trigger object detection
+detect_button = st.sidebar.button("Detect Objects")
+
+
+def perform_object_detection(image, model_name, threshold):
+    """
+    Perform object detection on the given image using the specified model and threshold.
+
+    Args:
+    image (PIL.Image): The image on which to perform object detection.
+    model_name (str): The name of the object detection model to use.
+    threshold (float): The threshold for object detection.
+
+    Returns:
+    PIL.Image, str: The image with drawn bounding boxes and a string of detected objects.
+    """
+    # Initialize the ObjectDetector
+    detector = ObjectDetector()
+    # Load the specified model
+    detector.load_model(model_name)
+    # Perform object detection
+    processed_image, detected_objects = detector.detect_objects(image, threshold)
+    return processed_image, detected_objects
+
+# Check if the 'Detect Objects' button was clicked
+if detect_button:
+    if image is not None:
+        # Open the uploaded image
+        image = Image.open(image)
+        # Display the original image
+        st.image(image, use_column_width=True, caption="Original Image")
+        # Perform object detection
+        processed_image, detected_objects = perform_object_detection(image, detect_model, threshold)
+        # Display the image with detected objects
+        st.image(processed_image, use_column_width=True, caption="Image with Detected Objects")
+        # Display the detected objects
+        st.write(detected_objects)
+    else:
+        st.write("Please upload an image for object detection.")