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app.py

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+import streamlit as st 
+from tensorflow.keras.models import load_model
+from PIL import Image
+import numpy as np
+
+model = load_model("model_traffic_sign.h5")
+
+def process_image(img):
+    img = img.convert('RGB')
+    img = img.resize((30,30))
+    img = np.array(img)
+    if img.ndim == 2:
+        img = np.stack((img,)*3, axis=-1)  # Convert grayscale to RGB if needed
+    img = img/255.0
+    img = np.expand_dims(img, axis=0)
+    return img
+
+st.title("TRAFFIC SIGN CLASSIFICATION:small_red_triangle:")
+st.header("Identify what each traffic sign means!")
+st.write("Upload your image and see the results")
+
+file = st.file_uploader("Choose an image", type=["jpg", "jpeg", "png", "webp"])
+
+if file is not None:
+    img = Image.open(file)
+    st.image(img, caption="Downloaded image")
+    image = process_image(img)
+    prediction = model.predict(image)
+    predicted_class = np.argmax(prediction)
+    
+    class_names = { 0:'Speed limit (20km/h)',
+            1:'Speed limit (30km/h)', 
+            2:'Speed limit (50km/h)', 
+            3:'Speed limit (60km/h)', 
+            4:'Speed limit (70km/h)', 
+            5:'Speed limit (80km/h)', 
+            6:'End of speed limit (80km/h)', 
+            7:'Speed limit (100km/h)', 
+            8:'Speed limit (120km/h)', 
+            9:'No passing', 
+            10:'No passing veh over 3.5 tons', 
+            11:'Right-of-way at intersection', 
+            12:'Priority road', 
+            13:'Yield', 
+            14:'Stop', 
+            15:'No vehicles', 
+            16:'Veh > 3.5 tons prohibited', 
+            17:'No entry', 
+            18:'General caution', 
+            19:'Dangerous curve left', 
+            20:'Dangerous curve right', 
+            21:'Double curve', 
+            22:'Bumpy road', 
+            23:'Slippery road', 
+            24:'Road narrows on the right', 
+            25:'Road work', 
+            26:'Traffic signals', 
+            27:'Pedestrians', 
+            28:'Children crossing', 
+            29:'Bicycles crossing',
+            30:'Beware of ice/snow',
+            31:'Wild animals crossing', 
+            32:'End speed + passing limits', 
+            33:'Turn right ahead', 
+            34:'Turn left ahead', 
+            35:'Ahead only', 
+            36:'Go straight or right', 
+            37:'Go straight or left', 
+            38:'Keep right', 
+            39:'Keep left', 
+            40:'Roundabout mandatory',
+            41:'End of no passing', 
+            42:'End no passing veh > 3.5 tons' }
+    
+    st.write(f"Predicted Traffic Sign: {class_names[predicted_class]}")

model_traffic_sign.h5

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+version https://git-lfs.github.com/spec/v1
+oid sha256:880de79cb3836fd1cd52b7d978e00ea54924c8ccd6520b6dd4f8095f97cc3968
+size 14102528

requirements.txt

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+streamlit
+tensorflow