Upload 3 files

embeddings.py

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+import os
+from tqdm import tqdm
+from glob import glob
+import numpy as np
+import cv2 as cv2
+import tempfile
+import insightface
+from insightface.app import FaceAnalysis
+from insightface.data  import get_image as ins_get_image
+
+def get_embeddings(db_dir):
+  app = FaceAnalysis(name='buffalo_l')
+  app.prepare(ctx_id=0, det_size=(640, 640),)
+  names = []
+  embeddings =  []
+
+  folders = os.listdir(f'db_dir/data/raw')
+  for folder in tqdm(folders):
+    if ".ipynb_checkpoints" in folder: continue
+    print(folder)
+    img_paths = glob(f'db_dir/data/raw/{folder}/*')
+    for img_path in img_paths:
+        img = cv2.imread(img_path)
+        if img is None: continue
+        faces = app.get(img)
+        if len(faces) != 1: continue
+        face = faces[0]
+        names.append(folder)
+        embeddings.append(face.normed_embedding)
+
+  embeddings = np.stack(embeddings, axis=0)
+  temp_dir = tempfile.mkdtemp()
+  np.save(os.path.join(temp_dir, "embeddings.npy"), embeddings)
+  np.save(os.path.join(temp_dir, "names.npy"), names)
+  return temp_dir
+

requirments.txt

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+opencv-python
+insightface
+numpy
+tdqm
+matplotlib
+pandas
+onnx==1.16.0
+onnxruntime==1.17.1

streamlit_app.py

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+import streamlit as st
+import os
+import cv2
+import numpy as np
+import tempfile
+import zipfile
+import shutil
+import embeddings
+
+def extract_database(zip_file):
+    # Create a temporary directory to extract the contents of the zip file
+    temp_dir = tempfile.mkdtemp()
+    with zipfile.ZipFile(zip_file, 'r') as zip_ref:
+        zip_ref.extractall(temp_dir)
+    return temp_dir
+
+
+#main function
+def main():
+    st.title("FACE FUSE")
+    tab_selection = st.sidebar.selectbox("Select Funtionality",["Embeddings","Immage Recognition","Video Recognition","Webcam Recognition"])
+    if tab_selection == "Embeddings":
+        st.header("Embeddings")
+        zip_file = st.file_uploader("Upload DataBase(ZIP)",type="zip")
+
+        if zip_file:
+            db_dir = extract_database(zip_file)
+            if st.button("Get Embeddings"):
+                temp_dir=embeddings.get_embeddings(db_dir)
+                embeddings_path = os.path.join(temp_dir, "embeddings.npy")
+                names_path = os.path.join(temp_dir, "names.npy")
+                st.write("Download numpy files:")
+                st.download_button(label="Download embeddings.npy", data=open(embeddings_path, "rb"), file_name="embeddings.npy")
+                st.download_button(label="Download names.npy", data=open(names_path, "rb"), file_name="names.npy")
+            shutil.rmtree(db_dir, ignore_errors=True)
+
+if __name__=="__main__":
+    main()