first commit

Author: cassiogiehl

.gitignore

@@ -158,3 +158,4 @@ cython_debug/
 #  and can be added to the global gitignore or merged into this file.  For a more nuclear
 #  option (not recommended) you can uncomment the following to ignore the entire idea folder.
 #.idea/
+.DS_Store

README.md

@@ -1 +1,19 @@
-# face_detection
+# Face Detection
+
+### To run the app follow the steps:
+
+```
+python3 -m venv venv 
+source venv/bin/activate
+pip3 install -r requirements.txt
+python3 face_detection_webcam.py
+```
+
+or
+
+```
+python3 -m venv venv 
+source venv/bin/activate
+pip3 install -r requirements.txt
+python3 face_detection_image.py
+```

face_detection_image.py

@@ -0,0 +1,45 @@
+import cv2
+import os
+
+
+def face_detection(casc_model, image_gray_scale):
+    # Detection frontal faces
+    faces_detected = casc_model.detectMultiScale(
+        image_gray_scale,
+        scaleFactor=1.5,
+        minNeighbors=7,
+        minSize=(30, 30),
+        flags = cv2.CASCADE_SCALE_IMAGE
+    )
+
+    qtd_faces = len(faces_detected)
+
+    if qtd_faces > 0:
+        print("Detected {0} faces!".format(qtd_faces))
+
+    return faces_detected, qtd_faces
+
+
+def draw_rectangle(faces, image):
+
+    for (x, y, w, h) in faces:
+        cv2.rectangle(image, (x, y), (x+w, y+h), (0, 255, 0), 2)
+
+
+casc_path_frontal_face = "xml/haarcascade_frontalface_default.xml"
+frontal_face_casc = cv2.CascadeClassifier(casc_path_frontal_face)
+
+files_in_path = os.listdir("images/")
+images = [image for image in files_in_path
+                if image.endswith(".jpeg")]
+
+for image in images:
+    image = cv2.imread(f"images/{ image }")
+
+    image_gray_scale = cv2.cvtColor(image, cv2.COLOR_BGR2GRAY)
+
+    frontal_faces, qtd_faces = face_detection(frontal_face_casc, image_gray_scale)
+    draw_rectangle(frontal_faces, image)
+
+    cv2.imshow(f'{ qtd_faces } face(s) detected', image)
+    cv2.waitKey(0)

face_detection_webcam.py

@@ -0,0 +1,44 @@
+import cv2
+
+casc_path_frontal_face = "xml/haarcascade_frontalface_default.xml"
+frontal_face_casc = cv2.CascadeClassifier(casc_path_frontal_face)
+
+video_capture = cv2.VideoCapture(0)
+
+def face_detection(casc_model, img_gray_scale):
+    # Detection frontal faces
+    faces_detected = casc_model.detectMultiScale(
+        img_gray_scale,
+        scaleFactor=1.5,
+        minNeighbors=7,
+        minSize=(30, 30),
+        flags = cv2.CASCADE_SCALE_IMAGE
+    )
+
+    qtd_faces = len(faces_detected)
+
+    if qtd_faces > 0:
+        print("Detected {0} faces!".format(qtd_faces))
+
+    return faces_detected
+
+def draw_rectangle(faces):
+
+    for (x, y, w, h) in faces:
+        cv2.rectangle(frame, (x, y), (x+w, y+h), (0, 255, 0), 2)
+
+while True:
+    ret, frame = video_capture.read()
+
+    img_gray_scale = cv2.cvtColor(frame, cv2.COLOR_BGR2GRAY)
+
+    frontal_faces = face_detection(frontal_face_casc, img_gray_scale)
+    draw_rectangle(frontal_faces)
+
+    cv2.imshow('face detection', frame)
+
+    if cv2.waitKey(1) & 0xFF == ord('q'):
+        break
+
+video_capture.release()
+cv2.destroyAllWindows()

images/pessoas.jpeg

@@ -0,0 +1,2 @@
+numpy==1.26.3
+opencv-python==4.9.0.80