Upload 3 files
Browse files- requirements.txt +5 -0
- run.sh +1 -0
- test.py +190 -0
requirements.txt
ADDED
@@ -0,0 +1,5 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
1 |
+
streamlit==1.19.0
|
2 |
+
Pillow==9.3.0
|
3 |
+
deepface==0.0.75
|
4 |
+
opencv-python-headless==4.6.0.66
|
5 |
+
pandas==1.5.3
|
run.sh
ADDED
@@ -0,0 +1 @@
|
|
|
|
|
1 |
+
streamlit run test.py
|
test.py
ADDED
@@ -0,0 +1,190 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
1 |
+
import streamlit as st
|
2 |
+
from PIL import Image
|
3 |
+
from deepface import DeepFace
|
4 |
+
import tempfile
|
5 |
+
import pandas as pd
|
6 |
+
import cv2 as cv
|
7 |
+
import threading
|
8 |
+
from time import sleep
|
9 |
+
|
10 |
+
st.title('Image Upload and Verification App')
|
11 |
+
|
12 |
+
st.write('Please upload two images for facial verification.')
|
13 |
+
|
14 |
+
# Upload two images
|
15 |
+
uploaded_file1 = st.file_uploader("Choose the first image...", type=["jpg", "png", "jpeg"], key="1")
|
16 |
+
uploaded_file2 = st.file_uploader("Choose the second image...", type=["jpg", "png", "jpeg"], key="2")
|
17 |
+
|
18 |
+
# Define the global variables
|
19 |
+
df = None
|
20 |
+
analyze_img1 = None
|
21 |
+
analyze_img2 = None
|
22 |
+
|
23 |
+
def verify(img1_path, img2_path):
|
24 |
+
global df
|
25 |
+
model_name = 'VGG-Face' # You can change this to other models like "Facenet", "OpenFace", "DeepFace", etc.
|
26 |
+
result = DeepFace.verify(img1_path=img1_path, img2_path=img2_path, model_name=model_name)
|
27 |
+
result["img1_facial_areas"] = result["facial_areas"]["img1"]
|
28 |
+
result["img2_facial_areas"] = result["facial_areas"]["img2"]
|
29 |
+
del result["facial_areas"]
|
30 |
+
df = pd.DataFrame([result])
|
31 |
+
|
32 |
+
def analyze_image1(img1_path):
|
33 |
+
global analyze_img1
|
34 |
+
analyze_img1 = DeepFace.analyze(img_path=img1_path)[0]
|
35 |
+
|
36 |
+
def analyze_image2(img2_path):
|
37 |
+
global analyze_img2
|
38 |
+
analyze_img2 = DeepFace.analyze(img_path=img2_path)[0]
|
39 |
+
|
40 |
+
def generate_analysis_sentence(analysis):
|
41 |
+
age = analysis['age']
|
42 |
+
gender = [i for i in analysis['gender'].keys()][-1]
|
43 |
+
dominant_emotion = analysis['dominant_emotion']
|
44 |
+
dominant_race = analysis['dominant_race']
|
45 |
+
|
46 |
+
# Highlight specific words in blue
|
47 |
+
age_html = f"<span style='color:blue'>{age}</span>"
|
48 |
+
gender_html = f"<span style='color:blue'>{gender}</span>"
|
49 |
+
dominant_emotion_html = f"<span style='color:blue'>{dominant_emotion}</span>"
|
50 |
+
dominant_race_html = f"<span style='color:blue'>{dominant_race}</span>"
|
51 |
+
|
52 |
+
return f"""The person in the image appears to be {age_html} years old, identified as '{gender_html}'.
|
53 |
+
The dominant emotion detected is {dominant_emotion_html}.
|
54 |
+
Ethnicity prediction indicates {dominant_race_html}."""
|
55 |
+
|
56 |
+
def display_image_with_analysis(image, analysis):
|
57 |
+
# Display the image
|
58 |
+
st.image(image, caption='Image', use_column_width=True)
|
59 |
+
|
60 |
+
# Display the analysis results
|
61 |
+
st.write("Analysis:")
|
62 |
+
st.markdown(generate_analysis_sentence(analysis), unsafe_allow_html=True)
|
63 |
+
|
64 |
+
def drow_rectangle():
|
65 |
+
# Load images with OpenCV
|
66 |
+
img1 = cv.imread(img1_path)
|
67 |
+
img2 = cv.imread(img2_path)
|
68 |
+
|
69 |
+
# Get facial areas and draw rectangles
|
70 |
+
face_area1 = df.iloc[0]["img1_facial_areas"]
|
71 |
+
p1_1 = (face_area1["x"], face_area1["y"])
|
72 |
+
p2_1 = (face_area1["x"] + face_area1["w"], face_area1["y"] + face_area1["h"])
|
73 |
+
rect_img1 = cv.rectangle(img1.copy(), p1_1, p2_1, (0, 255, 0), 2)
|
74 |
+
|
75 |
+
face_area2 = df.iloc[0]["img2_facial_areas"]
|
76 |
+
p1_2 = (face_area2["x"], face_area2["y"])
|
77 |
+
p2_2 = (face_area2["x"] + face_area2["w"], face_area2["y"] + face_area2["h"])
|
78 |
+
rect_img2 = cv.rectangle(img2.copy(), p1_2, p2_2, (0, 255, 0), 2)
|
79 |
+
|
80 |
+
# Resize images with a better interpolation method
|
81 |
+
rect_img1 = cv.cvtColor(rect_img1, cv.COLOR_BGR2RGB)
|
82 |
+
rect_img1 = cv.resize(rect_img1, (200, 250), interpolation=cv.INTER_AREA)
|
83 |
+
|
84 |
+
rect_img2 = cv.cvtColor(rect_img2, cv.COLOR_BGR2RGB)
|
85 |
+
rect_img2 = cv.resize(rect_img2, (200, 250), interpolation=cv.INTER_AREA)
|
86 |
+
|
87 |
+
#st.dataframe(df)
|
88 |
+
|
89 |
+
# Display the results
|
90 |
+
if df["verified"].iloc[0]:
|
91 |
+
message = "The faces in the images match!"
|
92 |
+
else:
|
93 |
+
message = "The faces in the images do not match!"
|
94 |
+
|
95 |
+
st.title(message)
|
96 |
+
|
97 |
+
col1, col2 = st.columns(2)
|
98 |
+
col1.image(rect_img1, caption='Verified Image 1', use_column_width=True)
|
99 |
+
col2.image(rect_img2, caption='Verified Image 2', use_column_width=True)
|
100 |
+
|
101 |
+
def get_analyze():
|
102 |
+
# Display the analysis results
|
103 |
+
st.write("Analysis for Image 1:")
|
104 |
+
try:
|
105 |
+
st.markdown(generate_analysis_sentence(analyze_img1), unsafe_allow_html=True)
|
106 |
+
except:
|
107 |
+
st.warning("can't detect image 1")
|
108 |
+
|
109 |
+
st.write("Analysis for Image 2:")
|
110 |
+
try:
|
111 |
+
st.markdown(generate_analysis_sentence(analyze_img2), unsafe_allow_html=True)
|
112 |
+
except:
|
113 |
+
st.warning("can't detect image 2")
|
114 |
+
|
115 |
+
|
116 |
+
col1, col2 = st.columns(2)
|
117 |
+
with col1:
|
118 |
+
st.text("Check if the faces in the images match!")
|
119 |
+
check = st.button("Check")
|
120 |
+
with col2:
|
121 |
+
st.text("Analyze the faces in each image!")
|
122 |
+
analyze = st.button("Analyze")
|
123 |
+
|
124 |
+
if uploaded_file1 is not None and uploaded_file2 is not None:
|
125 |
+
# Open the images with PIL
|
126 |
+
image1 = Image.open(uploaded_file1)
|
127 |
+
image2 = Image.open(uploaded_file2)
|
128 |
+
|
129 |
+
st.write("Here are your images:")
|
130 |
+
|
131 |
+
# Convert images to RGB if they are in RGBA mode
|
132 |
+
if image1.mode == 'RGBA':
|
133 |
+
image1 = image1.convert('RGB')
|
134 |
+
if image2.mode == 'RGBA':
|
135 |
+
image2 = image2.convert('RGB')
|
136 |
+
|
137 |
+
# Save the uploaded images to a temporary directory
|
138 |
+
with tempfile.NamedTemporaryFile(delete=False, suffix=".jpg") as tmp_file1:
|
139 |
+
image1.save(tmp_file1.name)
|
140 |
+
img1_path = tmp_file1.name
|
141 |
+
|
142 |
+
with tempfile.NamedTemporaryFile(delete=False, suffix=".jpg") as tmp_file2:
|
143 |
+
image2.save(tmp_file2.name)
|
144 |
+
img2_path = tmp_file2.name
|
145 |
+
|
146 |
+
t1 = threading.Thread(target=verify, args=(img1_path, img2_path))
|
147 |
+
t2 = threading.Thread(target=analyze_image1, args=(img1_path,))
|
148 |
+
t3 = threading.Thread(target=analyze_image2, args=(img2_path,))
|
149 |
+
t1.start()
|
150 |
+
t2.start()
|
151 |
+
t3.start()
|
152 |
+
t1.join()
|
153 |
+
|
154 |
+
|
155 |
+
if check and not t1.is_alive():
|
156 |
+
n = 0
|
157 |
+
while True:
|
158 |
+
try:
|
159 |
+
drow_rectangle()
|
160 |
+
sleep(2)
|
161 |
+
break
|
162 |
+
except:
|
163 |
+
n = n + 1
|
164 |
+
print(f"Try : {n}")
|
165 |
+
if n == 4:
|
166 |
+
st.warning("Please make sure there are people's faces in each of the two photos or try again")
|
167 |
+
break
|
168 |
+
|
169 |
+
t2.join()
|
170 |
+
t3.join()
|
171 |
+
if analyze:
|
172 |
+
n = 0
|
173 |
+
|
174 |
+
while t2.is_alive() or t3.is_alive():
|
175 |
+
sleep(2)
|
176 |
+
while True:
|
177 |
+
try:
|
178 |
+
get_analyze()
|
179 |
+
sleep(2)
|
180 |
+
break
|
181 |
+
except:
|
182 |
+
n = n + 1
|
183 |
+
print(f"Try : {n}")
|
184 |
+
if n == 4:
|
185 |
+
st.warning("Please make sure there are people's faces in each of the two photos or try again")
|
186 |
+
break
|
187 |
+
|
188 |
+
|
189 |
+
else:
|
190 |
+
st.write("Please upload both images to proceed.")
|