Update app.py

app.py

@@ -1,9 +1,10 @@
 import streamlit as st
+from ultralytics import YOLO
 from streamlit_option_menu import option_menu
 import tensorflow as tf
 import json
 from streamlit_lottie import st_lottie
-from PIL import Image
+from PIL import Image,ImageFont,ImageDraw
 from tensorflow.keras.models import load_model
 import numpy as np
 from tensorflow.keras.utils import custom_object_scope
@@ -23,6 +24,15 @@ def img_prep(paths):
         out.append(img)
     return out
 
+def img_prep_YOLO(paths,size):
+    out = []
+    for i in paths:
+        img = Image.open(i)
+        img = img.resize((size,size))
+        img = img.convert('RGB')
+        out.append(img)
+    return out
+
 def model_out(img,model_path):
     img = ((np.asarray(img))/127.5)-1
     img = np.expand_dims(img,0)
@@ -30,7 +40,26 @@ def model_out(img,model_path):
         model = load_model(model_path)
     pred = ((model.predict(img)+1)*127.5)/255
     return pred[0]
-    
+
+def yolo_out(model,img)
+    model = YOLO(model)
+    results = model(img)
+    for result in results:
+        cls = result.boxes.cls[0]
+        cls = arr[int(cls)]
+        lbl = result.boxes.conf[0]
+        boxes = result.boxes.xyxy[0]
+        draw = ImageDraw.Draw(img)
+        draw.rectangle([boxes[0], boxes[1], boxes[2], boxes[3]], outline="black", width=5)
+        text_position = (boxes[0]+boxes[2])/2, boxes[1]-10
+        draw.text(text_position, f'{cls} {lbl}', fill="red", font=font)
+
+    return img
+        
+font_size = 40
+font = ImageFont.truetype("arial.ttf", size=font_size)
+arr = ['A', 'B', 'C', 'D', 'E', 'F', 'G', 'H', 'I', 'J', 'K', 'L', 'M', 'N', 'O', 'P', 'Q', 'R', 'S', 'T', 'U', 'V', 'W', 'X', 'Y', 'Z']
+
 def lottiemaker(path):
     with open(path) as f:
         return json.load(f)
@@ -188,6 +217,26 @@ elif selected == 'Projects':
             st.image(model_out(imgs[0],'Portfolio Projects/FloodAreaSegmentationUnetPix2Pix.h5'),use_column_width=False)
         if img_selected_option == 'img2':
             st.image(model_out(imgs[1],'Portfolio Projects/FloodAreaSegmentationUnetPix2Pix.h5'),use_column_width=False)
+
+    if selected_option == 'YOLO object detection':
+        st.header('Description')
+        st.write('This is an YOLO mdoel which can detect different hand sign in an image')
+        st.header('Architecture')
+        st.write('The model uses YOLOv8 to do the detection')
+        
+        imgs = img_prep(['YOLOB.jpg','YOLOC.jpg'],416)
+        col1,col2 = st.columns(2)
+        with col1:
+            st.image(imgs[0],use_column_width=False)
+        with col2:
+            st.image(imgs[1],use_column_width=False)
+
+        img_options = {'img1':1, 'img2':2}
+        img_selected_option = st.selectbox('Select an Image', img_options)
+        if img_selected_option == 'img1':
+            st.image(model_out(imgs[0],'Portfolio Projects/HandSignDetector.pt'),use_column_width=False)
+        if img_selected_option == 'img2':
+            st.image(model_out(imgs[1],'Portfolio Projects/HandSignDetector.pt'),use_column_width=False)
             
     elif selected_option == 'Machine Learning Text classifier':