Added project

.gitignore

@@ -0,0 +1,129 @@
+# Byte-compiled / optimized / DLL files
+__pycache__/
+*.py[cod]
+*$py.class
+
+# C extensions
+*.so
+
+# Distribution / packaging
+.Python
+build/
+develop-eggs/
+dist/
+downloads/
+eggs/
+.eggs/
+lib/
+lib64/
+parts/
+sdist/
+var/
+wheels/
+pip-wheel-metadata/
+share/python-wheels/
+*.egg-info/
+.installed.cfg
+*.egg
+MANIFEST
+
+# PyInstaller
+#  Usually these files are written by a python script from a template
+#  before PyInstaller builds the exe, so as to inject date/other infos into it.
+*.manifest
+*.spec
+
+# Installer logs
+pip-log.txt
+pip-delete-this-directory.txt
+
+# Unit test / coverage reports
+htmlcov/
+.tox/
+.nox/
+.coverage
+.coverage.*
+.cache
+nosetests.xml
+coverage.xml
+*.cover
+*.py,cover
+.hypothesis/
+.pytest_cache/
+
+# Translations
+*.mo
+*.pot
+
+# Django stuff:
+*.log
+local_settings.py
+db.sqlite3
+db.sqlite3-journal
+
+# Flask stuff:
+instance/
+.webassets-cache
+
+# Scrapy stuff:
+.scrapy
+
+# Sphinx documentation
+docs/_build/
+
+# PyBuilder
+target/
+
+# Jupyter Notebook
+.ipynb_checkpoints
+
+# IPython
+profile_default/
+ipython_config.py
+
+# pyenv
+.python-version
+
+# pipenv
+#   According to pypa/pipenv#598, it is recommended to include Pipfile.lock in version control.
+#   However, in case of collaboration, if having platform-specific dependencies or dependencies
+#   having no cross-platform support, pipenv may install dependencies that don't work, or not
+#   install all needed dependencies.
+#Pipfile.lock
+
+# PEP 582; used by e.g. github.com/David-OConnor/pyflow
+__pypackages__/
+
+# Celery stuff
+celerybeat-schedule
+celerybeat.pid
+
+# SageMath parsed files
+*.sage.py
+
+# Environments
+.env
+.venv
+env/
+venv/
+ENV/
+env.bak/
+venv.bak/
+
+# Spyder project settings
+.spyderproject
+.spyproject
+
+# Rope project settings
+.ropeproject
+
+# mkdocs documentation
+/site
+
+# mypy
+.mypy_cache/
+.dmypy.json
+dmypy.json
+
+# Pyre type checker
+.pyre/

README.md

@@ -1,12 +1 @@
----
-title: AiOnIt
-emoji: 🐠
-colorFrom: yellow
-colorTo: indigo
-sdk: streamlit
-sdk_version: 1.2.0
-app_file: app.py
-pinned: false
----
-
-Check out the configuration reference at https://huggingface.co/docs/hub/spaces#reference
+# Ai-on-Iot

app.py

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+import streamlit as st 
+import pandas as pd
+import numpy as np
+import pickle
+import tensorflow as tf
+from pathlib import Path
+
+
+st.set_page_config(page_title="Traffic sign prediction", page_icon="⛔", layout='centered', initial_sidebar_state="collapsed")
+
+label_csv = pd.read_csv('./labels.csv', sep=',')
+labels = {row[1]['ClassId']:row[1]['Name'] for row in label_csv.iterrows()}
+print(labels)
+
+def main():
+    # title
+    html_temp = """
+    <div>
+    <h1 style="color:DarkRed;text-align:left;"> Traffic sign prediction  ⛔ </h1>
+    </div>
+    """
+    st.markdown(html_temp, unsafe_allow_html=True)
+
+    col1,col2  = st.columns([2,2])
+    
+    with col1: 
+        with st.expander(" ℹ️ Information", expanded=True):
+            st.write("""
+            Automatic traffic sign detection is an important role in self-driving car innovation.
+            """)
+
+    with col2:
+        df = pd.DataFrame()
+        upload_file = st.file_uploader("Choose a file of traffic sign.")
+
+        if upload_file is not None:
+            bytes_data = upload_file.getvalue()
+            fd = open("./img_to_predict.jpg", "wb")
+            fd.write(bytes_data)
+            fd.close()
+            st.image(bytes_data)
+        
+        if st.button('Predict'):
+            loaded_model = tf.keras.models.load_model("./model.h5", compile=True)
+            loaded_model.summary()
+            if Path("./img_to_predict.jpg").exists():
+                img = tf.keras.preprocessing.image.load_img("./img_to_predict.jpg", target_size=(128, 128), interpolation='lanczos')
+                img = tf.keras.preprocessing.image.img_to_array(img)
+                pred = loaded_model.predict(np.array([img]))
+                pred_label = np.argsort(pred)
+                for i in pred_label[0]:
+                    st.write(f"{labels[i]} : {pred[0][i]*100:0.2f} %")
+
+    st.warning("Note: This A.I application is for educational/demo purposes only and cannot be relied upon.")
+    hide_menu_style = """
+    <style>
+    #MainMenu {visibility: hidden;}
+    </style>
+    """
+
+hide_menu_style = """
+        <style>
+        #MainMenu {visibility: hidden;}
+        </style>
+        """
+st.markdown(hide_menu_style, unsafe_allow_html=True)
+
+if __name__ == '__main__':
+	main()

labels.csv

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+ClassId,Name
+0,Speed limit (5km/h)
+1,Speed limit (15km/h)
+2,Speed limit (30km/h)
+3,Speed limit (40km/h)
+4,Speed limit (50km/h)
+5,Speed limit (60km/h)
+6,Speed limit (70km/h)
+7,speed limit (80km/h)
+8,Dont Go straight or left
+9,Dont Go straight or Right
+10,Dont Go straight
+11,Dont Go Left
+12,Dont Go Left or Right
+13,Dont Go Right
+14,Dont overtake from Left
+15,No Uturn
+16,No Car
+17,No horn
+18,Speed limit (40km/h)
+19,Speed limit (50km/h)
+20,Go straight or right
+21,Go straight
+22,Go Left
+23,Go Left or right
+24,Go Right
+25,keep Left
+26,keep Right
+27,Roundabout mandatory
+28,watch out for cars
+29,Horn
+30,Bicycles crossing
+31,Uturn
+32,Road Divider
+33,Traffic signals
+34,Danger Ahead
+35,Zebra Crossing
+36,Bicycles crossing
+37,Children crossing
+38,Dangerous curve to the left
+39,Dangerous curve to the right
+40,Unknown1
+41,Unknown2
+42,Unknown3
+43,Go right or straight
+44,Go left or straight
+45,Unknown4
+46,ZigZag Curve
+47,Train Crossing
+48,Under Construction
+49,Unknown5
+50,Fences
+51,Heavy Vehicle Accidents
+52,Unknown6
+53,Give Way
+54,No stopping
+55,No entry
+56,Unknown7
+57,Unknown8

model.h5

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+version https://git-lfs.github.com/spec/v1
+oid sha256:a0ab4c0c9b40bfb1a08b7235223f1fd05037a40e04c384f566cedf002a336dbf
+size 39312536