Update src/streamlit_app.py

src/streamlit_app.py

@@ -1,40 +1,153 @@
-import altair as alt
-import numpy as np
-import pandas as pd
+# app.py
 import streamlit as st
+import cv2
+import numpy as np
+from PIL import Image
+import easyocr
+from streamlit_paste_button import paste_image_button as pbutton
+
+color_ranges = {
+    'fire': 'B50B0E',
+    'water': '015AB6',
+    'wind': '1F6A0B',
+    'earth': '623F23',
+    'light': 'DA8D09',
+    'dark': '502181'
+}
+
+def hex_to_rgb(hex_code):
+    return tuple(int(hex_code[i:i+2], 16) for i in (0, 2, 4))
+
+# 캐싱으로 Reader를 한 번만 로드
+@st.cache_resource
+def load_reader():
+    return easyocr.Reader(['en'], gpu=False, verbose=False)
+
+def extract_number(region, reader):
+    try:
+        gray = cv2.cvtColor(region, cv2.COLOR_BGR2GRAY)
+        resized = cv2.resize(gray, None, fx=6, fy=6, interpolation=cv2.INTER_CUBIC)
+        results = reader.readtext(resized, allowlist='0123456789', paragraph=False)
+
+        if results:
+            text = results[0][1]
+            return int(text.strip())
+    except Exception as e:
+        st.error(f"숫자 추출 오류: {e}")
+    return 0
+
+def find_items(img_array, color_range, reader):
+    img_rgb = cv2.cvtColor(img_array, cv2.COLOR_BGR2RGB)
+    results = {}
+
+    for type, hex_color in color_range.items():
+        target_rgb = hex_to_rgb(hex_color)
+        lower_c = np.array([max(0, c - 10) for c in target_rgb])
+        upper_c = np.array([min(255, c + 10) for c in target_rgb])
+        
+        mask = cv2.inRange(img_rgb, lower_c, upper_c)
+        contours, _ = cv2.findContours(mask, cv2.RETR_EXTERNAL, cv2.CHAIN_APPROX_SIMPLE)
+
+        if contours:
+            largest = max(contours, key=cv2.contourArea)
+            if cv2.contourArea(largest) > 100:
+                x, y, w, h = cv2.boundingRect(largest)
+                number_region = img_rgb[y+h:y+int(h*2), x+w:x+int(w*2.3)]
+                count = extract_number(number_region, reader)
+                results[type] = count
+            else:
+                results[type] = 0
+        else:
+            results[type] = 0
+
+    return results
+
+
+def process_image(img):
+    st.image(cv2.cvtColor(img, cv2.COLOR_BGR2RGB), caption='업로드된 이미지', use_container_width=True)
+    
+    with st.spinner('아이템 개수를 세는 중... (처음 실행시 모델 로딩으로 시간이 걸릴 수 있습니다)'):
+        try:
+            reader = load_reader()
+            results = find_items(img, color_ranges, reader)
+            
+            # 결과 표시
+            st.success('✅ 분석 완료!')
+            
+            col1, col2, col3 = st.columns(3)
+            
+            emoji_map = {
+                'fire': '🔥',
+                'water': '💧',
+                'wind': '💨',
+                'earth': '🌍',
+                'light': '✨',
+                'dark': '🌙'
+            }
+            
+            korean_map = {
+                'fire': '불',
+                'water': '물',
+                'wind': '바람',
+                'earth': '대지',
+                'light': '빛',
+                'dark': '어둠'
+            }
+
+            # 단일 열로 표시
+            for type, count in results.items():
+                st.metric(
+                    label=f"{emoji_map.get(type, '')} {korean_map.get(type, type)}", 
+                    value=f"{count}개"
+                )
+            
+            # cols = [col1, col2, col3]
+            # counts_str = ''
+            # for idx, (type, count) in enumerate(results.items()):
+            #     col = cols[idx % 3]
+            #     with col:
+            #         st.metric(
+            #             label=f"{emoji_map.get(type, '')} {korean_map.get(type, type)}", 
+            #             value=f"{count}개"
+            #         )
+                counts_str += f"{count}/"
+            st.markdown(f'{counts_str}')
+        except Exception as e:
+            st.error(f"분석 중 오류 발생: {e}")
+            st.info("EasyOCR 모델 로딩에 실패했을 수 있습니다. Streamlit Cloud의 메모리 제한 때문일 수 있습니다.")
+
+
+# Streamlit UI
+st.set_page_config(page_title="게임 아이템 카운터", page_icon="🎮")
+
+st.title('🎮 게임 아이템 카운터')
+st.write('획득한 속성 아이템 개수를 자동으로 세어드립니다!')
+
+tab1, tab2 = st.tabs(["📁 파일 업로드", "📋 붙여넣기"])
+
+with tab1:
+    st.write('이미지 파일을 업로드하세요')
+    uploaded_file = st.file_uploader("스크린샷을 업로드하세요", type=['png', 'jpg', 'jpeg'])
+
+    if uploaded_file is not None:
+        file_bytes = np.asarray(bytearray(uploaded_file.read()), dtype=np.uint8)
+        img = cv2.imdecode(file_bytes, cv2.IMREAD_COLOR)
+        process_image(img)
+
+with tab2:
+    st.write('이미지를 붙여넣으세요')
+    paste_result = pbutton(
+        label="📋 여기를 클릭하고 Ctrl+V",
+        background_color="#FF4B4B",
+        hover_background_color="#FF6B6B",
+    )
+
+    if paste_result.image_data is not None:
+        pil_image = paste_result.image_data
+        # st.markdown(f'{type(pil_image)}')
+        img = cv2.cvtColor(np.array(pil_image), cv2.COLOR_RGB2BGR)
+        process_image(img)
+
 
-"""
-# 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])),
-    ))
+st.markdown('---')
+st.caption('Made by ❤️sseong')