add app files

notebooks/app/Predict_photo.py

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+import pickle
+import customtkinter as ctk
+import os
+import cv2
+from PIL import Image
+from deepface import DeepFace
+from mtcnn import MTCNN
+from catboost import CatBoostClassifier
+import pandas as pd
+
+
+class Predict(ctk.CTkFrame):
+    def __init__(self, master):
+        super().__init__(master)
+        self.counter = 0
+        self.storage_name: str
+        self.grid_columnconfigure(0, weight=1)
+        self.detector = MTCNN()
+        self.catboost_model_usa = CatBoostClassifier()
+        self.catboost_model_usa.load_model("../catboost_usa.cbm")
+        self.catboost_model_ussr = CatBoostClassifier()
+        self.catboost_model_ussr.load_model("../catboost_ussr.cbm")
+        with open('../model/saved_dictionary.pkl', 'rb') as f:
+            self.name_usa = pickle.load(f)
+        with open('../model/saved_dictionary_russia.pkl', 'rb') as f:
+            self.name_ussr = pickle.load(f)
+        self.label = ctk.CTkLabel(self, text="Photo", fg_color="blue", text_color="white")
+        self.label.grid(row=0, column=0, sticky="ew")
+        self.button_get_dir = ctk.CTkButton(self, text="Choose folder", command=self.__open_file_dialog)
+        self.button_get_dir.grid(row=1, column=0, pady=10, sticky="ew")
+        self.button_start_predict = ctk.CTkButton(self, text="Start predict", command=self.__start_predict)
+        self.button_start_predict.grid(row=2, column=0, pady=10, sticky="ew")
+
+    def __open_file_dialog(self):
+        root = ctk.CTk()
+        root.withdraw()
+        file_path = ctk.filedialog.askdirectory(title='Choose image dataset')
+        if file_path != '':
+            root.destroy()
+            self.storage_name = file_path
+            self.iterator = iter(os.listdir(self.storage_name))
+            return file_path
+
+    def __start_predict(self):
+        if self.counter > 0:
+            self.label.destroy()
+        self.counter+=1
+        filename = next(self.iterator)
+        dicter3 = {}
+        if filename.endswith("png") or filename.endswith("jpg"):
+            print(filename)
+            img = cv2.cvtColor(cv2.imread(os.path.join(self.storage_name, filename)), cv2.COLOR_BGR2RGB)
+            img = cv2.resize(img, (1080, 720))
+            detections = self.detector.detect_faces(img)
+            if len(detections) > 1:
+                print(f'len detection = {len(detections)}')
+            for detection in detections:
+                confidence = detection["confidence"]#
+                if confidence > 0.9:
+                    x, y, w, h = detection["box"]
+                    detected_face = img[int(y):int(y + h), int(x):int(x + w)]##
+                    image = cv2.rectangle(img, (int(x), int(y)), (int(x+w), int(y+h)), (255, 0, 0), 2)
+                    embedding = DeepFace.represent(detected_face, model_name='Facenet', enforce_detection=False)
+                    ebd = embedding[0]["embedding"]
+                    dicter3[1] = ebd
+                    data_usa = pd.DataFrame.from_dict(dicter3.items())
+                    data_usa.rename(columns={0: "id", 1: "embd"}, inplace=True, errors="ignore")
+                    new_cols = pd.DataFrame(data_usa['embd'].apply(pd.Series))
+                    df_usa = pd.concat([data_usa, new_cols], axis=1)
+                    df_usa.drop(["embd"], axis=1, inplace=True, errors="ignore")
+                    X = df_usa.drop(["id"], axis=1)
+                    result = self.catboost_model_usa.predict(X)
+                    result_ussr = self.catboost_model_ussr.predict(X)
+                    index_usa = result[0][0]
+                    index_ussr = result_ussr[0][0]
+                    for images in os.listdir(f'C://Users//fatik//PycharmProjects//UfaHack2024//data//actors_usa//{index_usa}'):
+                        image_usa = cv2.imread(os.path.join(f'C://Users//fatik//PycharmProjects//UfaHack2024//data//actors_usa//{index_usa}', images))
+                        break
+                    for images in os.listdir(f'C://Users//fatik//PycharmProjects//UfaHack2024//data//actors_ussr_russia//{index_ussr}'):
+                        image_ussr = cv2.imread(os.path.join(f'C://Users//fatik//PycharmProjects//UfaHack2024//data//actors_ussr_russia//{index_ussr}', images))
+                        break
+                    image[0:128, 0:128] = cv2.resize(cv2.cvtColor(image_usa, cv2.COLOR_BGR2RGB), (128,128))
+                    image[0:128, 138:266] = cv2.resize(cv2.cvtColor(image_ussr, cv2.COLOR_BGR2RGB), (128,128))
+                    self.image = Image.fromarray(image)
+                    self.image_tk = ctk.CTkImage(self.image, size=(self.image.width, self.image.height))
+                    self.label = ctk.CTkLabel(self, image=self.image_tk, text=self.name_usa[result[0][0]], text_color="red")
+                    self.label.grid(row=3, column=0, pady=10, sticky="ew")
+