init

test/display.py

+import cv2
+
+print(cv2.getBuildInformation())
+video_capture = cv2.VideoCapture("rtsp://118.173.233.110:5551/Streaming/Channels/1")
+
+while True:
+	if video_capture.isOpened():
+		ret, frame = video_capture.read()
+		cv2.imshow('Video', frame)
+
+	if cv2.waitKey(1) & 0xFF == ord('q'):
+        	break
+
+video_capture.release()
+cv2.destroyAllWindows()

test/face.py

+import face_recognition
+import cv2
+import os
+import re
+import requests
+import math
+import base64
+
+
+def send_to_bigstream(name,dist,feature,ba64frame,ba64lab):
+    #requests.get('http://push02.igridproject.info/lsrface?name=' + name + '&distance=' + str(dist))
+    requests.post('http://push02.igridproject.info/lsrface', json={"name": name,"distance":dist,"feature":feature,"img_raw":ba64frame,"img_label":ba64lab})
+
+def image_files_in_folder(folder):
+    return [os.path.join(folder, f) for f in os.listdir(folder) if re.match(r'.*\.(jpg|jpeg|png)', f, flags=re.I)]
+
+def load_face_db(known_people_folder):
+    known_names = []
+    known_face_encodings = []
+    db = []
+    rec = {}
+
+    for file in image_files_in_folder(known_people_folder):
+        basename = os.path.splitext(os.path.basename(file))[0]
+        img = face_recognition.load_image_file(file)
+        encodings = face_recognition.face_encodings(img)
+
+        print 'loading facedb >> ' + basename
+
+        if len(encodings) > 1:
+            click.echo("WARNING: More than one face found in {}. Only considering the first face.".format(file))
+
+        if len(encodings) == 0:
+            click.echo("WARNING: No faces found in {}. Ignoring file.".format(file))
+        else:
+            #known_names.append(basename)
+            #known_face_encodings.append(encodings[0])
+            rec = {'name':basename.split('_')[0],'face_encoding':encodings[0]}
+            db.append(rec)
+
+    return db
+
+def find_face(face_db,prefer_face):
+    res=False
+    dist=1
+    name='unknown'
+
+    for rec in face_db:
+        dd = face_recognition.face_distance(rec['face_encoding'],[prefer_face])
+        if dd[0] < dist:
+            res=True
+            dist=dd[0]
+            name=rec['name']
+
+        if dist > 0.5:
+            res=False
+
+    return {'match':res,'name':name,'distance':dist}
+
+def label_frame(frame,face_locations,face_names):
+    labframe = frame
+    # Display the results
+    for (top, right, bottom, left), name in zip(face_locations, face_names):
+        # Scale back up face locations since the frame we detected in was scaled to 1/2 size
+        top *= 1
+        right *= 1
+        bottom *= 1
+        left *= 1
+
+        # Draw a box around the face
+        cv2.rectangle(labframe, (left, top), (right, bottom), (0, 0, 255), 1)
+
+        # Draw a label with a name below the face
+        #cv2.rectangle(frame, (left, bottom - 35), (right, bottom), (0, 0, 255), cv2.FILLED)
+        font = cv2.FONT_HERSHEY_DUPLEX
+        cv2.putText(labframe, name, (left + 0, bottom + 18), font, 0.5, (255, 255, 255), 1)
+
+    # Display the resulting image
+    #cv2.imshow('Video', frame)
+    return labframe
+
+def frame2ba64(frame):
+
+    cnt = cv2.imencode('.jpg',frame)[1]
+    ba64 = base64.b64encode(cnt)
+
+    return ba64
+
+######################################################################################
+###################################### Main ##########################################
+
+# Get a reference to webcam #0 (the default one)
+video_capture = cv2.VideoCapture(0)
+video_capture.set(3,960)
+video_capture.set(4,720)
+
+#video_capture = cv2.VideoCapture('rtsp://127.0.0.1:5551/Streaming/Channels/1')
+#video_capture.set(3,960)
+#video_capture.set(4,720)
+
+face_folder = '/home/igrid/facedb/known'
+facedb = load_face_db(face_folder)
+
+# Initialize some variables
+face_locations = []
+face_encodings = []
+face_names = []
+process_this_frame = True
+
+known_people = 'unknown'
+scan_ratio = 0.75
+
+frame_delay=5
+while True:
+    # Grab a single frame of video
+    ret, frame = video_capture.read()
+
+    # Resize frame of video to 1/2 size for faster face recognition processing
+    small_frame = cv2.resize(frame, (0, 0), fx=scan_ratio, fy=scan_ratio)
+    #small_frame = frame
+
+    # Only process every other frame of video to save time
+    if process_this_frame:
+        # Find all the faces and face encodings in the current frame of video
+        small_face_locations = face_recognition.face_locations(small_frame)
+        face_locations = []
+        for (lt,lr,lb,ll) in small_face_locations:
+            locat = ( int(math.ceil(lt/scan_ratio)),int(math.ceil(lr/scan_ratio)),int(math.ceil(lb/scan_ratio)),int(math.ceil(ll/scan_ratio)) )
+            face_locations.append(locat)
+
+        face_encodings = face_recognition.face_encodings(frame, face_locations)
+        face_names = []
+        found_people = ("unknown",1,[])
+        for face_encoding in face_encodings:
+            # See if the face is a match for the known face(s)
+
+            result = find_face(facedb,face_encoding)
+            lname = "unknown"
+
+            if result['match']:
+                lname = result['name'] + ' ' + "{:3.2f}".format((1-result['distance'])*100) + '%'
+                found_people = (result['name'],result['distance'],face_encoding)
+            else:
+                found_people = ("unknown",1,face_encoding)
+
+            face_names.append(lname)
+
+        if found_people[0] != known_people and len(face_encodings) == 1:
+            ba64frame = frame2ba64(frame)
+            ba64lab = frame2ba64(label_frame(frame,face_locations,face_names))
+
+            if found_people[0] != "unknown":
+                frame_delay = 5
+
+            if found_people[0] != "unknown" or frame_delay==0:
+                print 'found => ' + found_people[0]
+                known_people = found_people[0]
+                fea = [x for x in found_people[2]]
+                send_to_bigstream(found_people[0],found_people[1],fea,ba64frame,ba64lab)
+
+
+        if frame_delay > 0:
+            frame_delay = frame_delay-1
+
+
+    process_this_frame = not process_this_frame
+
+
+
+
+    # Hit 'q' on the keyboard to quit!
+    if cv2.waitKey(1) & 0xFF == ord('q'):
+        break
+
+# Release handle to the webcam
+video_capture.release()
+cv2.destroyAllWindows()