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Dockerfile

@@ -1,21 +1,21 @@
-FROM python:3.9-slim
-
-WORKDIR /app
-
-RUN apt-get update && apt-get install -y \
-    build-essential \
-    curl \
-    software-properties-common \
-    git \
-    && rm -rf /var/lib/apt/lists/*
-
-COPY requirements.txt ./
-COPY src/ ./src/
-
-RUN pip3 install -r requirements.txt
-
-EXPOSE 8501
-
-HEALTHCHECK CMD curl --fail http://localhost:8501/_stcore/health
-
+FROM python:3.9-slim
+
+WORKDIR /app
+
+RUN apt-get update && apt-get install -y \
+    build-essential \
+    curl \
+    software-properties-common \
+    git \
+    && rm -rf /var/lib/apt/lists/*
+
+COPY requirements.txt ./
+COPY src/ ./src/
+
+RUN pip3 install -r requirements.txt
+
+EXPOSE 8501
+
+HEALTHCHECK CMD curl --fail http://localhost:8501/_stcore/health
+
 ENTRYPOINT ["streamlit", "run", "src/streamlit_app.py", "--server.port=8501", "--server.address=0.0.0.0"]

README.md

@@ -1,19 +1,19 @@
----
-title: Type Of Cap
-emoji: 🚀
-colorFrom: red
-colorTo: red
-sdk: docker
-app_port: 8501
-tags:
-- streamlit
-pinned: false
-short_description: Streamlit template space
----
-
-# Welcome to Streamlit!
-
-Edit `/src/streamlit_app.py` to customize this app to your heart's desire. :heart:
-
-If you have any questions, checkout our [documentation](https://docs.streamlit.io) and [community
-forums](https://discuss.streamlit.io).
+---
+title: Type Of Cap
+emoji: 🚀
+colorFrom: red
+colorTo: red
+sdk: docker
+app_port: 8501
+tags:
+- streamlit
+pinned: false
+short_description: Streamlit template space
+---
+
+# Welcome to Streamlit!
+
+Edit `/src/streamlit_app.py` to customize this app to your heart's desire. :heart:
+
+If you have any questions, checkout our [documentation](https://docs.streamlit.io) and [community
+forums](https://discuss.streamlit.io).

requirements.txt

@@ -1,3 +1,3 @@
-altair
-pandas
+altair
+pandas
 streamlit

src/prediction.py

@@ -0,0 +1,78 @@
+import streamlit as st
+import pandas as pd
+import os
+import sys
+from io import BytesIO, StringIO
+import pickle
+import json
+import tensorflow as tf
+from PIL import Image
+import numpy as np
+
+# load files
+
+model=tf.keras.models.load_model('best_model.h5')
+
+klas = ['baseball_cap', 'beanie_hat', 'bucket_hat', 'fedora_hat', 'flat_cap']
+
+st.title('Jenis Topi')
+
+picup = st.file_uploader('Upload a picture', type=['jpg', 'jpeg', 'png'])
+
+if picup is not None:
+    st.image(picup, caption='Uploaded Image', use_column_width=True)
+
+    if st.button('Predict'):
+
+        img = Image.open(picup).convert('RGB')
+        img = img.resize((400,400))
+        img_array = np.array(img)
+        img_array = np.expand_dims(img_array, axis=0)
+
+        prediction = model.predict(img_array)
+        pred_index = np.argmax(prediction)
+        pred_class = klas[pred_index]
+        confidence = prediction[0][pred_index]*100
+
+        st.success(f'Prediction: **{pred_class}** ({confidence:.2f}% confidence)')
+
+# class picupload(object):
+
+#     def __init__(self):
+#         self.fileTypes=['jpg']
+
+#     def run(self):
+#         topi = st.file_uploader('Upload picture', type=self.fileTypes)
+#         show_file = st.empty()
+#         if not topi:
+#             show_file.info('Please upload a picture')
+#             return
+#         content = topi.getvalue()
+#         if isinstance(topi, BytesIO):
+#             show_file.image(topi)
+#         topi.close()
+
+# if __name__ == '__main__':
+#     helper = picupload()
+#     helper.run()
+
+# def run():
+    
+#     with st.form(key='type-of-cap'):
+
+#         st.write('##Topi')
+
+#         topi = st.file_uploader('Upload file', type=['jpg'])
+#         show_topi = st.empty()
+
+#         if not topi:
+#             show_topi.info('Please upload a picture : {}'.format(' '.join(['jpg'])))
+#             return
+#         content = topi.getvalue()
+
+#         if isinstance(topi, BytesIO):
+#             show_topi.image(topi)
+#         topi.close()
+
+# run()
+        

src/streamlit_app.py

@@ -1,40 +1,40 @@
-import altair as alt
-import numpy as np
-import pandas as pd
-import streamlit as st
-
-"""
-# Welcome to Streamlit!
-
-Edit `/streamlit_app.py` to customize this app to your heart's desire :heart:.
-If you have any questions, checkout our [documentation](https://docs.streamlit.io) and [community
-forums](https://discuss.streamlit.io).
-
-In the meantime, below is an example of what you can do with just a few lines of code:
-"""
-
-num_points = st.slider("Number of points in spiral", 1, 10000, 1100)
-num_turns = st.slider("Number of turns in spiral", 1, 300, 31)
-
-indices = np.linspace(0, 1, num_points)
-theta = 2 * np.pi * num_turns * indices
-radius = indices
-
-x = radius * np.cos(theta)
-y = radius * np.sin(theta)
-
-df = pd.DataFrame({
-    "x": x,
-    "y": y,
-    "idx": indices,
-    "rand": np.random.randn(num_points),
-})
-
-st.altair_chart(alt.Chart(df, height=700, width=700)
-    .mark_point(filled=True)
-    .encode(
-        x=alt.X("x", axis=None),
-        y=alt.Y("y", axis=None),
-        color=alt.Color("idx", legend=None, scale=alt.Scale()),
-        size=alt.Size("rand", legend=None, scale=alt.Scale(range=[1, 150])),
+import altair as alt
+import numpy as np
+import pandas as pd
+import streamlit as st
+
+"""
+# Welcome to Streamlit!
+
+Edit `/streamlit_app.py` to customize this app to your heart's desire :heart:.
+If you have any questions, checkout our [documentation](https://docs.streamlit.io) and [community
+forums](https://discuss.streamlit.io).
+
+In the meantime, below is an example of what you can do with just a few lines of code:
+"""
+
+num_points = st.slider("Number of points in spiral", 1, 10000, 1100)
+num_turns = st.slider("Number of turns in spiral", 1, 300, 31)
+
+indices = np.linspace(0, 1, num_points)
+theta = 2 * np.pi * num_turns * indices
+radius = indices
+
+x = radius * np.cos(theta)
+y = radius * np.sin(theta)
+
+df = pd.DataFrame({
+    "x": x,
+    "y": y,
+    "idx": indices,
+    "rand": np.random.randn(num_points),
+})
+
+st.altair_chart(alt.Chart(df, height=700, width=700)
+    .mark_point(filled=True)
+    .encode(
+        x=alt.X("x", axis=None),
+        y=alt.Y("y", axis=None),
+        color=alt.Color("idx", legend=None, scale=alt.Scale()),
+        size=alt.Size("rand", legend=None, scale=alt.Scale(range=[1, 150])),
     ))