Create app.py

app.py

@@ -0,0 +1,33 @@
+import streamlit as st
+from pipeline import detectPipeline
+
+
+st.title('Sign Language Letters detection')
+st.write('Detects Sign language Alphabets in an image \nPowered by YOLOv8 Nano model')
+
+st.write('')
+
+detect_pipeline = detectPipeline()
+
+st.info('Sign Language Letters detection model loaded successfully!')
+
+uploaded_file = st.file_uploader("Upload an image", type=["jpg", "png", "jpeg"])
+
+if uploaded_file is not None:
+    
+    with st.container():
+        col1, col2 = st.columns([3, 3])
+        
+        col1.header('Input Image')
+        col1.image(uploaded_file, caption='Uploaded Image', use_column_width=True)
+
+        col1.text('')
+        col1.text('')
+
+        if st.button('Detect'):
+            detections = detect_pipeline.detect_signs(img_path=uploaded_file)
+            detections_img = detect_pipeline.drawDetections2Image(img_path=uploaded_file, detections=detections)
+
+            col2.header('Detections')
+            col2.image(detections_img, caption='Predictions by model', use_column_width=True)
+