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pyproject.toml

@@ -0,0 +1,19 @@
+[project]
+name = "parentclosetesting"
+version = "0.1.0"
+description = "Add your description here"
+readme = "README.md"
+requires-python = ">=3.13"
+dependencies = [
+    "deepface>=0.0.100",
+    "insightface>=1.0.1",
+    "numpy>=2.5.0",
+    "onnxruntime>=1.27.0",
+    "opencv-python-headless>=4.13.0.92",
+    "pillow>=12.2.0",
+    "streamlit>=1.58.0",
+    "tf-keras>=2.21.0",
+    "torch>=2.12.1",
+    "torchvision>=0.27.1",
+    "transformers>=5.12.1",
+]

src/streamlit_app.py

@@ -1,110 +1,152 @@
-import sys
-import os
-import tempfile
-
-import streamlit as st
-
-sys.path.insert(0, os.path.dirname(os.path.abspath(__file__)))
-
-st.set_page_config(
-    page_title="More Close To Whom?",
-    page_icon="👨‍👩‍👧",
-    layout="wide",
-)
-
-st.title("👨‍👩‍👧 More Close To Whom?")
-st.caption("Upload photos of father, mother, and child to discover who the child resembles more")
-
-# Backend selector
-backend_choice = st.radio(
-    "ML Backend",
-    ["🧠 DeepFace", "⚡ InsightFace", "🤗 HF Model"],
-    horizontal=True,
-    help="Select the AI model to use for face analysis",
-)
-
-st.divider()
-
-# Upload row: Father | Child (center, wider) | Mother
-col_f, col_c, col_m = st.columns([1, 1.3, 1])
-
-with col_f:
-    st.markdown("#### 👨 Father")
-    father_file = st.file_uploader(
-        "Upload father photo", type=["jpg", "jpeg", "png"], key="father", label_visibility="collapsed"
-    )
-    if father_file:
-        st.image(father_file, use_container_width=True)
-
-with col_c:
-    st.markdown("#### 🧒 Child")
-    child_file = st.file_uploader(
-        "Upload child photo", type=["jpg", "jpeg", "png"], key="child", label_visibility="collapsed"
-    )
-    if child_file:
-        st.image(child_file, use_container_width=True)
-
-with col_m:
-    st.markdown("#### 👩 Mother")
-    mother_file = st.file_uploader(
-        "Upload mother photo", type=["jpg", "jpeg", "png"], key="mother", label_visibility="collapsed"
-    )
-    if mother_file:
-        st.image(mother_file, use_container_width=True)
-
-st.divider()
-
-all_uploaded = all([father_file, child_file, mother_file])
-
-if st.button("▶ Analyze Resemblance", type="primary", disabled=not all_uploaded):
-    with st.spinner("Analyzing faces — this may take a moment on first run..."):
-        with tempfile.TemporaryDirectory() as tmpdir:
-            def save(uploaded, name):
-                path = os.path.join(tmpdir, name)
-                with open(path, "wb") as f:
-                    f.write(uploaded.getvalue())
-                return path
-
-            father_path = save(father_file, "father.jpg")
-            mother_path = save(mother_file, "mother.jpg")
-            child_path = save(child_file, "child.jpg")
-
-            try:
-                if "DeepFace" in backend_choice:
-                    from backends.deepface_backend import analyze
-                elif "InsightFace" in backend_choice:
-                    from backends.insightface_backend import analyze
-                else:
-                    from backends.hf_backend import analyze
-
-                result = analyze(father_path, mother_path, child_path)
-
-                st.success("Analysis complete!")
-
-                r1, r2, r3 = st.columns(3)
-                with r1:
-                    st.metric("👨 Father resemblance", f"{result['father_score']}%")
-                    st.progress(result["father_score"] / 100)
-                with r2:
-                    st.metric("👩 Mother resemblance", f"{result['mother_score']}%")
-                    st.progress(result["mother_score"] / 100)
-                with r3:
-                    st.metric("🧒 Estimated child age", f"{result['age']} yrs")
-
-                st.divider()
-
-                diff = abs(result["father_score"] - result["mother_score"])
-                if diff < 2:
-                    st.info("⚖️ Child resembles both parents almost equally!")
-                elif result["father_score"] >= result["mother_score"]:
-                    st.success(f"✅ Child looks more like **Father 👨** ({diff:.1f}% difference)")
-                else:
-                    st.success(f"✅ Child looks more like **Mother 👩** ({diff:.1f}% difference)")
-
-            except ValueError as e:
-                st.error(f"⚠️ {e}")
-            except Exception as e:
-                st.error(f"❌ Analysis failed: {e}")
-
-elif not all_uploaded:
-    st.info("👆 Please upload photos of all three family members to begin")
+import sys
+import os
+import tempfile
+
+import streamlit as st
+
+sys.path.insert(0, os.path.dirname(os.path.abspath(__file__)))
+
+st.set_page_config(
+    page_title="More Close To Whom?",
+    page_icon="👨‍👩‍👧",
+    layout="wide",
+)
+
+st.title("👨‍👩‍👧 More Close To Whom?")
+st.caption("Upload photos of father, mother, and child to discover who the child resembles more")
+
+# Backend selector
+backend_choice = st.radio(
+    "ML Backend",
+    ["🧠 DeepFace", "⚡ InsightFace", "🤗 HF Model"],
+    horizontal=True,
+    help="Select the AI model to use for face analysis",
+)
+
+st.divider()
+
+# Upload row: Father | Child (center, wider) | Mother
+col_f, col_c, col_m = st.columns([1, 1.3, 1])
+
+with col_f:
+    st.markdown("#### 👨 Father")
+    tab1, tab2 = st.tabs(["📁 Upload", "📷 Camera"])
+    with tab1:
+        upload = st.file_uploader(
+            "Upload Father Image",
+            type=["jpg", "jpeg", "png","webp"],
+            key="father_upload",
+            label_visibility="collapsed",
+        )
+
+    with tab2:
+        camera = st.camera_input(
+            "Capture Father Image",
+            key="father_camera",
+            label_visibility="collapsed",
+        )
+
+    father_file = camera if camera else upload
+    if father_file:
+        st.image(father_file, use_container_width=True)
+
+with col_c:
+    st.markdown("#### 🧒 Child")
+    tab1, tab2 = st.tabs(["📁 Upload", "📷 Camera"])
+    with tab1:
+        upload = st.file_uploader(
+            "Upload child photo",
+            type=["jpg", "jpeg", "png","webp"],
+            key="child_upload",
+            label_visibility="collapsed",
+        )
+
+    with tab2:
+        camera = st.camera_input(
+            "Capture child photo",
+            key="child_camera",
+            label_visibility="collapsed",
+        )
+
+    child_file = camera if camera else upload
+    if child_file:
+        st.image(child_file, use_container_width=True)
+
+with col_m:
+    st.markdown("#### 👩 Mother")
+    tab1, tab2 = st.tabs(["📁 Upload", "📷 Camera"])
+    with tab1:
+        upload = st.file_uploader(
+            "Upload mother photo",
+            type=["jpg", "jpeg", "png","webp"],
+            key="mother_upload",
+            label_visibility="collapsed",
+        )
+
+    with tab2:
+        camera = st.camera_input(
+            "Capture mother photo",
+            key="mother_camera",
+            label_visibility="collapsed",
+        )
+
+    mother_file = camera if camera else upload
+    if mother_file:
+        st.image(mother_file, use_container_width=True)
+
+st.divider()
+
+all_uploaded = all([father_file, child_file, mother_file])
+
+if st.button("▶ Analyze Resemblance", type="primary", disabled=not all_uploaded):
+    with st.spinner("Analyzing faces — this may take a moment on first run..."):
+        with tempfile.TemporaryDirectory() as tmpdir:
+            def save(uploaded, name):
+                path = os.path.join(tmpdir, name)
+                with open(path, "wb") as f:
+                    f.write(uploaded.getvalue())
+                return path
+
+            father_path = save(father_file, "father.jpg")
+            mother_path = save(mother_file, "mother.jpg")
+            child_path  = save(child_file, "child.jpg")
+
+            try:
+                if "DeepFace" in backend_choice:
+                    from backends.deepface_backend import analyze
+                elif "InsightFace" in backend_choice:
+                    from backends.insightface_backend import analyze
+                else:
+                    from backends.hf_backend import analyze
+
+                result = analyze(father_path, mother_path, child_path)
+
+                st.success("Analysis complete!")
+
+                r1, r2, r3 = st.columns(3)
+                with r1:
+                    st.metric("👨 Father resemblance", f"{result['father_score']}%")
+                    st.progress(result["father_score"] / 100)
+                with r2:
+                    st.metric("👩 Mother resemblance", f"{result['mother_score']}%")
+                    st.progress(result["mother_score"] / 100)
+                with r3:
+                    st.metric("🧒 Estimated child age", f"{result['age']} yrs")
+
+                st.divider()
+
+                diff = abs(result["father_score"] - result["mother_score"])
+                if diff < 2:
+                    st.info("⚖️ Child resembles both parents almost equally!")
+                elif result["father_score"] >= result["mother_score"]:
+                    st.success(f"✅ Child looks more like **Father 👨** ({diff:.1f}% difference)")
+                else:
+                    st.success(f"✅ Child looks more like **Mother 👩** ({diff:.1f}% difference)")
+
+            except ValueError as e:
+                st.error(f"⚠️ {e}")
+            except Exception as e:
+                st.error(f"❌ Analysis failed: {e}")
+
+elif not all_uploaded:
+    st.info("👆 Please upload photos of all three family members to begin")