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.gitattributes

@@ -33,3 +33,5 @@ saved_model/**/* filter=lfs diff=lfs merge=lfs -text
 *.zip filter=lfs diff=lfs merge=lfs -text
 *.zst filter=lfs diff=lfs merge=lfs -text
 *tfevents* filter=lfs diff=lfs merge=lfs -text
+Resnet_2024_0214_version1 filter=lfs diff=lfs merge=lfs -text
+sample.mp4 filter=lfs diff=lfs merge=lfs -text

README.md

@@ -1,10 +1,10 @@
 ---
-title: Personal Color
-emoji: 👀
-colorFrom: gray
+title: PersonalColor
+emoji: 🐨
+colorFrom: indigo
 colorTo: yellow
 sdk: streamlit
-sdk_version: 1.32.2
+sdk_version: 1.31.1
 app_file: app.py
 pinned: false
 license: other

Resnet_2024_0214_version1

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:192babd1d7bd112e9a080efcd4689324ec009b6eab28eedc1bcbe2002dabbb54
+size 233519466

app.py

@@ -0,0 +1,91 @@
+from torchvision import models, transforms
+from PIL import Image
+import torch
+import torch.nn as nn
+import io
+import streamlit as st
+import time
+
+st.title("パーソナルカラー予測")
+
+SIZE = 224
+MEAN = (0.485, 0.456, 0.406)
+STD = (0.229, 0.224, 0.225)
+
+transform = transforms.Compose([
+    transforms.Resize((SIZE, SIZE)),
+    transforms.ToTensor(),
+    transforms.Normalize(MEAN, STD),
+])
+
+model = models.resnet152(pretrained=True)
+n_classes = 4
+num_ftrs = model.fc.in_features
+model.fc = nn.Linear(num_ftrs, n_classes)
+device = torch.device("cuda" if torch.cuda.is_available() else "cpu")
+model.load_state_dict(torch.load('Resnet_2024_0214_version1', map_location=device))
+model.to(device)
+model.eval()
+view_flag = True
+skip = False
+
+left_column, right_column = st.columns(2)
+
+def predict_image(img):
+    img = img.convert('RGB')
+    img_transformed = transform(img)
+    inputs = img_transformed.unsqueeze(0).to(device)
+    with torch.no_grad():
+        outputs = model(inputs)
+        _, preds = torch.max(outputs, 1)
+    return preds.item()
+uploaded_file = st.file_uploader('Choose an image...', type=['jpg', 'png'])
+if uploaded_file:
+    with left_column:
+        img = Image.open(uploaded_file)
+        st.image(img, caption="Uploaded Image", use_column_width=True)
+        pred = predict_image(img)
+    if pred == 0:
+        season_type = "秋"
+    elif pred == 1:
+        season_type = "春"
+    elif pred == 2:
+        season_type = "夏"
+    else:
+        season_type = "冬"
+    if 'show_video' not in st.session_state:
+        st.session_state.show_video = False
+    if 'skip' not in st.session_state:
+        st.session_state.skip = False
+
+    person_result = st.selectbox(
+        '結果の修正',
+        ('春', '夏', '秋', '冬')
+    )
+
+    if person_result:
+        season_type = person_result
+
+    with left_column:
+        st.write(f"パーソナルカラーは {season_type} です")
+
+        # おすすめの商品を見るボタン
+        view_recommend = st.button("おすすめの商品を見る")
+    with right_column:
+        if view_recommend:
+            st.session_state.show_video = True
+
+        # スキップされずに動画を表示する
+        if st.session_state.show_video and not st.session_state.skip:
+            st.video("sample.mp4", start_time=0)
+
+        # 動画のスキップボタンが押されたら、レコメンド文を表示する
+        if st.session_state.show_video and not st.session_state.skip:
+            time.sleep(5)
+            st.session_state.show_video = False
+            st.session_state.skip = True
+        if st.session_state.skip:
+            st.write(
+                """
+                レコメンド文です。
+                """)

requirements.txt

@@ -0,0 +1,6 @@
+torch
+torchvision
+Pillow
+streamlit
+numpy
+pillow

sample.mp4

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:ae9354277c8b3a4e72086b7f721d899ffd9c9b4aa0f6b8a99fa389d67b3ab8bb
+size 3640717