add application

.idea/.gitignore

@@ -0,0 +1,8 @@
+# Default ignored files
+/shelf/
+/workspace.xml
+# Editor-based HTTP Client requests
+/httpRequests/
+# Datasource local storage ignored files
+/dataSources/
+/dataSources.local.xml

.idea/Background_Removal_and_Change.iml

@@ -0,0 +1,10 @@
+<?xml version="1.0" encoding="UTF-8"?>
+<module type="PYTHON_MODULE" version="4">
+  <component name="NewModuleRootManager">
+    <content url="file://$MODULE_DIR$">
+      <excludeFolder url="file://$MODULE_DIR$/venvme" />
+    </content>
+    <orderEntry type="jdk" jdkName="Python 3.9 (pythonProject)" jdkType="Python SDK" />
+    <orderEntry type="sourceFolder" forTests="false" />
+  </component>
+</module>

.idea/deployment.xml

@@ -0,0 +1,14 @@
+<?xml version="1.0" encoding="UTF-8"?>
+<project version="4">
+  <component name="PublishConfigData" serverName="HAHALOLO_SERVER" remoteFilesAllowedToDisappearOnAutoupload="false">
+    <serverData>
+      <paths name="HAHALOLO_SERVER">
+        <serverdata>
+          <mappings>
+            <mapping local="$PROJECT_DIR$" web="/" />
+          </mappings>
+        </serverdata>
+      </paths>
+    </serverData>
+  </component>
+</project>

.idea/inspectionProfiles/Project_Default.xml

@@ -0,0 +1,27 @@
+<component name="InspectionProjectProfileManager">
+  <profile version="1.0">
+    <option name="myName" value="Project Default" />
+    <inspection_tool class="PyPackageRequirementsInspection" enabled="true" level="WARNING" enabled_by_default="true">
+      <option name="ignoredPackages">
+        <value>
+          <list size="14">
+            <item index="0" class="java.lang.String" itemvalue="scipy" />
+            <item index="1" class="java.lang.String" itemvalue="opencv-python" />
+            <item index="2" class="java.lang.String" itemvalue="Pillow" />
+            <item index="3" class="java.lang.String" itemvalue="pandas" />
+            <item index="4" class="java.lang.String" itemvalue="datetime" />
+            <item index="5" class="java.lang.String" itemvalue="tensorflow" />
+            <item index="6" class="java.lang.String" itemvalue="retina-face" />
+            <item index="7" class="java.lang.String" itemvalue="gdown" />
+            <item index="8" class="java.lang.String" itemvalue="matplotlib" />
+            <item index="9" class="java.lang.String" itemvalue="deepface" />
+            <item index="10" class="java.lang.String" itemvalue="cmake" />
+            <item index="11" class="java.lang.String" itemvalue="keras" />
+            <item index="12" class="java.lang.String" itemvalue="requests" />
+            <item index="13" class="java.lang.String" itemvalue="numpy" />
+          </list>
+        </value>
+      </option>
+    </inspection_tool>
+  </profile>
+</component>

.idea/inspectionProfiles/profiles_settings.xml

@@ -0,0 +1,6 @@
+<component name="InspectionProjectProfileManager">
+  <settings>
+    <option name="USE_PROJECT_PROFILE" value="false" />
+    <version value="1.0" />
+  </settings>
+</component>

.idea/misc.xml

@@ -0,0 +1,4 @@
+<?xml version="1.0" encoding="UTF-8"?>
+<project version="4">
+  <component name="ProjectRootManager" version="2" project-jdk-name="Python 3.9 (pythonProject)" project-jdk-type="Python SDK" />
+</project>

.idea/modules.xml

@@ -0,0 +1,8 @@
+<?xml version="1.0" encoding="UTF-8"?>
+<project version="4">
+  <component name="ProjectModuleManager">
+    <modules>
+      <module fileurl="file://$PROJECT_DIR$/.idea/Background_Removal_and_Change.iml" filepath="$PROJECT_DIR$/.idea/Background_Removal_and_Change.iml" />
+    </modules>
+  </component>
+</project>

.idea/sshConfigs.xml

@@ -0,0 +1,8 @@
+<?xml version="1.0" encoding="UTF-8"?>
+<project version="4">
+  <component name="SshConfigs">
+    <configs>
+      <sshConfig authType="PASSWORD" host="10.10.15.87" id="8b67aa76-bd20-4263-bc45-270bf4ea8b6e" port="22" nameFormat="DESCRIPTIVE" username="root" useOpenSSHConfig="true" />
+    </configs>
+  </component>
+</project>

.idea/vcs.xml

@@ -0,0 +1,9 @@
+<?xml version="1.0" encoding="UTF-8"?>
+<project version="4">
+  <component name="VcsDirectoryMappings">
+    <mapping directory="$PROJECT_DIR$" vcs="Git" />
+    <mapping directory="$PROJECT_DIR$/Background_removal_and_change" vcs="Git" />
+    <mapping directory="$PROJECT_DIR$/Remove-Photo-Background-using-TensorFlow" vcs="Git" />
+    <mapping directory="$PROJECT_DIR$/yolov5" vcs="Git" />
+  </component>
+</project>

.idea/webServers.xml

@@ -0,0 +1,14 @@
+<?xml version="1.0" encoding="UTF-8"?>
+<project version="4">
+  <component name="WebServers">
+    <option name="servers">
+      <webServer id="7c3f60f5-5354-4ef4-a283-182d579b3fe7" name="HAHALOLO_SERVER">
+        <fileTransfer rootFolder="/storage/test" accessType="SFTP" host="10.10.15.87" port="22" sshConfigId="8b67aa76-bd20-4263-bc45-270bf4ea8b6e" sshConfig="[email protected]:22 password">
+          <advancedOptions>
+            <advancedOptions dataProtectionLevel="Private" keepAliveTimeout="0" passiveMode="true" shareSSLContext="true" />
+          </advancedOptions>
+        </fileTransfer>
+      </webServer>
+    </option>
+  </component>
+</project>

README.md

@@ -1,13 +1 @@
----
-title: Background Removal And Change
-emoji: 🐢
-colorFrom: pink
-colorTo: red
-sdk: streamlit
-sdk_version: 1.10.0
-app_file: app.py
-pinned: false
-license: other
----
-
-Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference
+# Background_removal_and_change

app.py

@@ -0,0 +1,92 @@
+from libs import *
+from utils_func import create_dir, main_processing
+
+
+
+create_dir("tempDir")
+
+def load_image(image_file):
+	img = Image.open(image_file)
+	return img
+
+
+def streamlit_app():
+    detection_model_path = "weight_files/clothes_detection_model.pt"
+    background_model_path = "weight_files/model.h5"
+    # save_path = ""
+    image_file = None
+    st.title("""WELCOME TO MY APP""")
+    st.subheader("""FOR BACKGROUND REMOVAL AND CHANGE!""")
+    col1 = None
+    col2 = None
+    final_img = None
+    with st.spinner("[UPLOAD] Image uploading"):
+        try:
+            image_file = st.file_uploader('[UPLOAD] Please upload your image:', type=["png", "jpg", "jpeg"])
+            time.sleep(1)
+        except:
+            print("[ERROR] Sorry, something went wrong!")
+            pass
+    # print(type(image_file))
+
+    if image_file is not None:
+        st.success("Load image successfully!...")
+        image = load_image(image_file)
+        # print(type(image))
+        col1, col2, col3 = st.columns(3)
+        with col1:
+            st.image(image, caption="Image before processing")
+        save_path = "tempDir\\"+ image_file.name
+        image.save(save_path)
+
+
+        image_path, details = save_path, image_file
+
+        if details is not None:
+            with col2:
+                with st.spinner("[PROCESSING] Image processing"):
+                    final_img_path = main_processing(col1, col2, col3, sport_bg_path=stadium_sport_bg_path, swim_bg_path=beach_swim_bg_path,
+                                          office_bg_path=office_bg_path, img_path=image_path, name=details.name,
+                                          detection_model_path=detection_model_path,
+                                          background_model_path=background_model_path)
+                    time.sleep(1)
+
+            with col1:
+                if final_img_path is not None:
+                        final_img = load_image(final_img_path)
+                        st.image(final_img, caption="Image after processing")
+                        st.balloons()
+                        with col2:
+                            with open(final_img_path, "rb") as file:
+                                st.write('\n')
+                                st.write('\n')
+                                st.write('\n')
+                                st.write('\n')
+                                st.write('\n')
+
+                                file_name = final_img_path.split("\\")[-1].split(".")[-2]
+                                if st.download_button(
+                                    label="Download postprocessing image",
+                                    data=file,
+                                    file_name= file_name,
+                                    mime="image/png"
+                                ):
+                                    st.success('[DOWNLOAD] Download sucessfully!')
+
+
+
+if __name__ == '__main__':
+    np.random.seed(42)
+    tf.random.set_seed(42)
+
+    bg_path = ""
+    background_model_path = "weight_files\\model.h5"
+    detection_model_path = "weight_files\\clothes_detection_model.pt"
+
+    stadium_sport_bg_path = "backgrounds\\camnou_stadium.jpg"
+    beach_swim_bg_path = "backgrounds\\beach.jpg"
+    office_bg_path = "backgrounds\\office-bg.jpg"
+
+    image_path = None
+
+    streamlit_app()

libs.py

@@ -0,0 +1,10 @@
+import torch
+import json
+import os
+import numpy as np
+import cv2
+import tensorflow as tf
+import streamlit as st
+import time
+from PIL import Image
+from tensorflow.keras.utils import CustomObjectScope

metrics.py

@@ -0,0 +1,23 @@
+
+import numpy as np
+import tensorflow as tf
+from tensorflow.keras import backend as K
+
+def iou(y_true, y_pred):
+    def f(y_true, y_pred):
+        intersection = (y_true * y_pred).sum()
+        union = y_true.sum() + y_pred.sum() - intersection
+        x = (intersection + 1e-15) / (union + 1e-15)
+        x = x.astype(np.float32)
+        return x
+    return tf.numpy_function(f, [y_true, y_pred], tf.float32)
+
+smooth = 1e-15
+def dice_coef(y_true, y_pred):
+    y_true = tf.keras.layers.Flatten()(y_true)
+    y_pred = tf.keras.layers.Flatten()(y_pred)
+    intersection = tf.reduce_sum(y_true * y_pred)
+    return (2. * intersection + smooth) / (tf.reduce_sum(y_true) + tf.reduce_sum(y_pred) + smooth)
+
+def dice_loss(y_true, y_pred):
+    return 1.0 - dice_coef(y_true, y_pred)

run_app.py

@@ -0,0 +1,11 @@
+import uvicorn
+from fastapi import FastAPI
+
+app = FastAPI()
+
+@app.get("/")
+def home():
+    return {"Hello": "World"}
+
+if __name__ == "__main__":
+    uvicorn.run("hello_world_fastapi:app")

utils_func.py

@@ -0,0 +1,205 @@
+from metrics import dice_loss, dice_coef, iou
+from libs import *
+
+
+os.environ["TF_CPP_MIN_LOG_LEVEL"] = "2"
+
+""" Global parameters """
+H = 512
+W = 512
+
+
+def load_image(image_file):
+	img = Image.open(image_file)
+	return img
+
+
+def choose_background(col1, col2, col3):
+    background_file = None
+    bg_image = None
+    with col3:
+        with st.spinner("[UPLOAD] Background uploading"):
+            try:
+                if background_file is None:
+                    try:
+                        background_file = st.file_uploader('[UPLOAD] Please upload your background:', type=["png", "jpg", "jpeg"])
+                        time.sleep(1)
+                    except:
+                        pass
+            except:
+                print("[ERROR] Sorry, something went wrong!")
+                pass
+
+    if background_file is not None:
+        with col2:
+            st.success("Load background successfully!...")
+
+        bg_image = load_image(background_file)
+        print(type(bg_image))
+        save_path = "backgrounds\\" + background_file.name
+        bg_image.save(save_path)
+
+        return bg_image, save_path
+
+
+def create_dir(path):
+    if not os.path.exists(path):
+        os.makedirs(path)
+
+
+def check_clothe(model_path, img_path):
+    # Model
+    model = torch.hub.load('ultralytics/yolov5', 'custom', model_path)  # or yolov5n - yolov5x6, custom
+
+    # Inference
+    results = model(img_path)
+
+    # Results
+    new_results = results.pandas().xyxy[0].sort_values("confidence").to_json(orient="records")
+    new_results = json.loads(new_results)
+
+    classes_in_img = []
+    classes_count_dict = {}
+    item = ''
+    if len(new_results) != 0:
+        for i in range(len(new_results)):
+            classes_in_img.append(new_results[i]['name'])
+        set_of_classes = set(classes_in_img)
+        list_of_classes = list(set_of_classes)
+
+        older_value_count = 0
+        for idx in range(len(list_of_classes)):
+            value_count = classes_in_img.count(list_of_classes[idx])
+            if value_count > older_value_count:
+                item = list_of_classes[idx]
+
+    else:
+        item = None
+
+    return item
+
+
+
+def main_processing(col1, col2, col3, sport_bg_path, swim_bg_path, office_bg_path, img_path, name, detection_model_path, background_model_path):
+    """ Seeding """
+    bg_path = None
+    np.random.seed(42)
+    tf.random.set_seed(42)
+
+    model_path = detection_model_path
+
+    stadium_sport_bg_path = sport_bg_path
+    beach_swim_bg_path = swim_bg_path
+    office_bg_path = office_bg_path
+
+    """ Directory for storing files """
+    create_dir("remove_bg")
+
+    st.write('Auto detect or choosing background? ')
+
+    if bg_path is None:
+        if st.checkbox('Choose background'):
+            try:
+                bg_img, save_path = choose_background(col1, col2, col3)
+                bg_path = save_path
+            except:
+                pass
+
+            """ Directory for storing files """
+        elif st.checkbox('Automatic background'):
+            item = check_clothe(model_path, img_path)
+            if item == 'sport':
+                bg_path = stadium_sport_bg_path
+                st.write("Hãy tiếp tục luyện tập TDTT chăm chỉ nhé!...")
+            if item == 'swim':
+                bg_path = beach_swim_bg_path
+                st.write("Thời tiết thế này không đi biển hơi phí nhé!...")
+            if item == 'office':
+                bg_path = office_bg_path
+                st.write("Chơi nhiều roài, đi làm chăm chỉ thuii...")
+            if item == None:
+                st.warning("Sorry, mô hình chúng tôi không biết bạn đang mặc cái quái gì hết...")
+                st.warning("Chọn background bạn muốn nhé!")
+                try:
+                    background_img, save_path = choose_background(col1, col2, col3)
+                    bg_path = save_path
+                except:
+                    pass
+
+            else:
+                pass
+
+        else:
+            pass
+
+    if bg_path is not None:
+        """ Loading model: DeepLabV3+ """
+        with CustomObjectScope({'iou': iou, 'dice_coef': dice_coef, 'dice_loss': dice_loss}):
+            model = tf.keras.models.load_model(background_model_path)
+
+        """ Read the image """
+        image = cv2.imread(img_path, cv2.IMREAD_COLOR)
+        h, w, _ = image.shape
+        x = cv2.resize(image, (W, H))
+        x = x / 255.0
+        x = x.astype(np.float32)
+        x = np.expand_dims(x, axis=0)
+
+        """ Prediction """
+        y = model.predict(x)[0]
+        y = cv2.resize(y, (w, h))
+        y = np.expand_dims(y, axis=-1)
+        y = y > 0.5
+
+        photo_mask = y
+        background_mask = np.abs(1 - y)
+        cv2.imwrite(
+            f"remove_bg\\{name}_1.png",
+            photo_mask * 255)
+        cv2.imwrite(
+            f"remove_bg\\{name}_2.png",
+            background_mask * 255)
+
+        cv2.imwrite(
+            f"remove_bg\\{name}_3.png",
+            image * photo_mask)
+        cv2.imwrite(
+            f"remove_bg\\{name}_4.png",
+            image * background_mask)
+
+        bg_img = cv2.imread(bg_path, cv2.IMREAD_COLOR)
+        print(bg_img.shape)
+        new_bg_img = cv2.resize(bg_img, (w, h))
+
+        new_new_bg_img = new_bg_img * background_mask
+
+        cv2.imwrite(
+            f"remove_bg\\{name}_5.png",
+            new_new_bg_img)
+
+        final_final_img = new_new_bg_img + image * photo_mask
+
+        final_img_path = f"remove_bg\\{name}_6.png"
+        cv2.imwrite(
+            final_img_path,
+            final_final_img)
+
+        return final_img_path
+
+
+# if __name__ == '__main__':
+#     """ Seeding """
+#     np.random.seed(42)
+#     tf.random.set_seed(42)
+#
+#     bg_path = ""
+#     background_model_path = "weight_files\\model.h5"
+#     detection_model_path = "weight_files\\clothes_detection_model.pt"
+#
+#     stadium_sport_bg_path = "backgrounds\\camnou_stadium.jpg"
+#     beach_swim_bg_path = "backgrounds\\beach.jpg"
+#     office_bg_path = "backgrounds\\office-bg.jpg"
+#
+#     img_path = "images\\truong-van-bang-10163832.jpg"
+#
+#     main(sport_bg_path=stadium_sport_bg_path, swim_bg_path=beach_swim_bg_path, office_bg_path=office_bg_path, name="a", img_path=img_path, detection_model_path=detection_model_path, background_model_path=background_model_path)

weight_files/clothes_detection_model.pt

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:2a66f97acde7f676689cf65dd11175becebc2c35167bdbe47d0e610283eaa605
+size 173184733

weight_files/model.h5

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:60a1b798e58cd022f78e891e94fa1b1dcbd84ca9d574d43ecfe50b678a31c6d1
+size 215146600