Upload 7 files

.gitattributes

@@ -33,3 +33,4 @@ saved_model/**/* filter=lfs diff=lfs merge=lfs -text
 *.zip filter=lfs diff=lfs merge=lfs -text
 *.zst filter=lfs diff=lfs merge=lfs -text
 *tfevents* filter=lfs diff=lfs merge=lfs -text
+vid1.mp4 filter=lfs diff=lfs merge=lfs -text

app.py

@@ -0,0 +1,37 @@
+import streamlit as st
+from ultralytics import YOLO
+import os
+from PIL import Image
+
+# Load the model
+model = YOLO('models/best.pt')
+
+# Streamlit UI
+st.title("Object Detection with Ultralytics")
+
+st.markdown(
+    """
+    <style>
+    #MainMenu {visibility: hidden;}
+    footer {visibility: hidden;}
+    .ezrtsby0 {visibility: hidden;}
+    </style>
+    """,
+    unsafe_allow_html=True
+)
+
+# Upload image
+uploaded_file = st.file_uploader("Choose an image", type=["jpg", "jpeg", "png"])
+
+if uploaded_file is not None:
+    # Read the uploaded image
+    image = Image.open(uploaded_file)
+
+    # Perform object detection
+    result = model.predict(source=image, conf=0.2,save=True)
+    img_save_path = "output/"
+    
+    for r in result : r.save(filename= img_save_path + uploaded_file.name) 
+
+    # Display the output image
+    st.image(img_save_path+uploaded_file.name, caption="Detected Objects", use_column_width=True)

requirements.txt

@@ -0,0 +1,3 @@
+streamlit
+ultralytics
+Pillow

vid1.mp4

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:d31a8d40a9ee2d02ab0fe4632c2581e8bcceb2750563db0da0876ed8f875f5fc
+size 3622242