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get paraVISION working again

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This commit is contained in:
carl 2024-10-22 22:25:43 -03:00
parent 241372ef00
commit 4266448f68
3 changed files with 69 additions and 32 deletions
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4
src/faceclass.py
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@ -252,7 +252,9 @@ class FaceClass(object):
# @doc crop an image, allowing a gutter.
def shrink(self, name, skale=0.5):
print ("shrinking ",name)
print ("shrinking ",name,skale)
if skale == 0:
return
self.imgs[name] = cv2.resize(self.imgs[name],None,fx=skale,fy=skale)

87
src/paravisionx.py
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@ -3,21 +3,32 @@
#
import json
import sys
import os
import cv2
import torchvision.transforms
### export PYTHONPATH=/wherever/yoloserv/modules ... as long as "paravision/.../" is in there
from paravision.recognition.exceptions import ParavisionException
from paravision.recognition.engine import Engine
from paravision.recognition.sdk import SDK
from paravision.recognition.engine import Engine
import paravision.recognition.utils as pru
#from openvino.inference_engine import Engineq
#from openvino.inference_engine import Engineq
#from deepface.basemodels import VGGFace, OpenFace, Facenet, FbDeepFace, DeepID
from faceclass import FaceClass
# Paravision is quite unlike all the other open source img recognition packages
# which cause problems when image formats move between the two.
# So this class has quite a few differences.
class Paravision(FaceClass):
models = {}
scores = {}
quality = {}
sdk = None
match_score = 0
def init(self,backend=None,model=None):
print("@@@ initialising paravision")
try:
@ -26,6 +37,18 @@ class Paravision(FaceClass):
pass
# @doc Load a pic using the device label
def load1(self, name,fname):
print(" Loading image '%s' from file %s" % (name, fname))
if not os.path.isfile(fname):
print(" * file not found: %s" % (fname))
return '{ "status":442565, "remark":"file name not found", "guilty_param":"fname", "guilty_value":"%s" }' % (fname)
self.files[name] = fname
self.imgs[name] = pru.load_image(fname)
print(" Loaded %s from file %s" % (name, fname))
return '{ "status":0, "remark":"OK", "name":"%s", "fname":"%s" }' % (name,fname)
# @doc find all the faces in the named image
def detect(self, name):
boxes = []
@ -33,47 +56,59 @@ class Paravision(FaceClass):
print("** face_recognition::detect ... %s" % name)
try:
# Get all faces from images with qualities, landmarks, and embeddings
res = self.sdk.get_faces([self.imgs[name]])
boxes = res.faces
for b in boxes:
b = b.bounding_box
#print(b)
self.boxes.append((int(b.origin.x),int(b.origin.y),int(b.origin.x+b.width),int(b.origin.y+b.height)))
print("found %d boxes for %s" % (len(self.boxes), name) )
faces = self.sdk.get_faces([self.imgs[name]], qualities=True, landmarks=True, embeddings=True)
inferences = faces.image_inferences
ix = inferences[0].most_prominent_face_index()
self.models[name] = inferences[0].faces[ix].embedding
self.quality[name] = round(1000*inferences[0].faces[ix].quality)
self.boxes = [ (0,0,0,0) ]
except Exception as ex:
self.errstr = "image processing exception at get_faces: "+str(ex)
return '{ "status":222310, "remark":"image processing exception", "guilty_param":"error", "guilty_value":"%s" }' % str(ex)
return '{ "status":0, "remark":"OK", "faces":%d, "boxes":%s }' % (len(self.boxes), json.dumps(self.boxes))
# @doc This does everything for you.
# If you are smartserv, "crowd" means cam and "govid" means regula pic
def crowd_vs_govid(self, name1,file1,scale1, name2,file2,scale2):
print("##1##")
if self.json2obj(self.load1(name1, file1))["status"] != 0:
return self.jsonx
if self.json2obj(self.detect(name1))["status"] != 0:
return self.jsonx
self.save(name1,"/tmp")
print("##2##")
if self.json2obj(self.load1(name2, file2))["status"] != 0:
return self.jsonx
self.save(name2,"/tmp")
if self.json2obj(self.detect(name2))["status"]!=0:
return self.jsonx
self.save(name2,"/tmp")
print("##R##")
jsonstr = self.compare(name1,name2)
print(jsonstr)
return jsonstr
# @doc compare two named images, previously loaded
def compare(self, name1, name2):
print("** face_recognition::compare ... %s vs %s" % (name1,name2))
self.encs[name1] = self.sdk.get_embedding_from_prepared_image(self.imgs[name1])
self.encs[name2] = self.sdk.get_embedding_from_prepared_image(self.imgs[name2])
#if self.encs[name1]==[]:
# return '{ "status":14330, "remark":"could not encode image", "guilty_param":"img1", "guilty_value":"%s" }' % name1
#if self.encs[name2]==[]:
# return '{ "status":14331, "remark":"could not encode image", "guilty_param":"img2", "guilty_value":"%s" }' % name2
print(self.encs.keys())
print(self.encs[name1])
print(self.encs[name2])
try:
res = self.sdk.get_match_score(self.model, other.model)
res = self.sdk.get_match_score(self.models[name1], self.models[name2])
print("Match is ",res)
#self.match_score = 1000 * (1 - face_recognition.face_distance([self.encs[name1][0]], self.encs[name2][0]))
#print("Score is ",self.match_score)
# Create .json
self.tree["score"] = self.match_score[0]
self.match_score = res
except Exception as ex:
print("** paravision::compare exception ... " + str(ex) )
self.errstr = "image comparison exception at compute_scores: "+str(ex)
return '{ "status":332410, "remark":"%s" }' % self.errstr
return '{ "status":0, "remark":"OK", "score":%d }' % self.match_score[0]
return '{ "status":0, "remark":"OK", "score":%d }' % self.match_score
def scores(self):
return '{ "status":0, "remark":"OK", "score":%d }' % self.match_score
if __name__ == '__main__':

8
src/yoloserv.py
View File

@ -240,12 +240,12 @@ class yoloserv(object):
# Match faces together
@cherrypy.expose
def svc_match_faces(self,dev1,fil1,scl1,dev2,fil2,scl2):
jsonstr = self.facematcher.crowd_vs_govid(dev1,self.conf["yolo_indir"]+fil1,scl1, dev2,self.conf["yolo_outdir"]+fil2,scl2)
def svc_match_faces(self,dev1,fil1,scl1s,dev2,fil2,scl2s):
scl1 = float(scl1s)
scl2 = float(scl2s)
jsonstr = self.facematcher.crowd_vs_govid(dev1,self.conf["yolo_indir"]+fil1,scl1, dev2,self.conf["yolo_indir"]+fil2,scl2)
obj = self.json2obj(jsonstr)
return jsonstr
if obj.status > 0:
return jsonstr
def json2obj(self,jsonx):
return json.loads(jsonx)