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para test

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Ox 2024-10-21 17:48:09 -03:00
parent b69c4f9ecc
commit 0ea955674a
1 changed files with 35 additions and 15 deletions
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src/paravisionx.py
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@ -3,7 +3,7 @@
# #
import json import json
import sys import sys
import numpy as np
### export PYTHONPATH=/wherever/yoloserv/modules ... as long as "paravision/.../" is in there ### export PYTHONPATH=/wherever/yoloserv/modules ... as long as "paravision/.../" is in there
from paravision.recognition.exceptions import ParavisionException from paravision.recognition.exceptions import ParavisionException
from paravision.recognition.engine import Engine from paravision.recognition.engine import Engine
@ -47,31 +47,51 @@ class Paravision(FaceClass):
# @doc compare two named images, previously loaded # @doc compare two named images, previously loaded
def compare(self, name1, name2): def compare(self, name1, name2):
print("** face_recognition::compare ... %s vs %s" % (name1,name2)) print("** paravision::compare ... %s vs %s" % (name1, name2))
# Ensure the image is reshaped to match the expected input size (e.g., (1, 3, 112, 112))
def adjust_image_shape(img, target_shape=(1, 3, 112, 112)):
img_shape = img.shape
# If image shape doesn't match target, adjust it (resize, pad, or reshape as needed)
if img_shape != target_shape:
print(f"Adjusting image shape from {img_shape} to {target_shape}")
# Resize or pad as necessary to match the target shape
img = np.resize(img, target_shape) # Resizes without preserving aspect ratio (can be modified if needed)
return img
# Adjust the shape of both images
self.imgs[name1] = adjust_image_shape(self.imgs[name1])
self.imgs[name2] = adjust_image_shape(self.imgs[name2])
# Get embeddings using the Paravision SDK
self.encs[name1] = self.sdk.get_embedding_from_prepared_image(self.imgs[name1]) 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]) 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 # Debug: Print the encodings
#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.keys())
print(self.encs[name1]) print(self.encs[name1])
print(self.encs[name2]) print(self.encs[name2])
try:
res = self.sdk.get_match_score(self.model, other.model)
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 try:
self.tree["score"] = self.match_score[0] # Assuming 'self.model' and 'other.model' are defined elsewhere in your code
res = self.sdk.get_match_score(self.model, other.model)
print("Match is ", res)
# Store the result in self.tree
self.tree["score"] = res # Assuming 'res' is the match score
except Exception as ex: except Exception as ex:
print("** paravision::compare exception ... " + str(ex) ) print("** paravision::compare exception ... " + str(ex))
self.errstr = "image comparison exception at compute_scores: "+str(ex) self.errstr = "image comparison exception at compute_scores: " + str(ex)
return '{ "status":332410, "remark":"%s" }' % self.errstr return '{ "status":332410, "remark":"%s" }' % self.errstr
return '{ "status":0, "remark":"OK", "score":%d }' % self.match_score[0]
# Return success with the match score
return '{ "status":0, "remark":"OK", "score":%d }' % self.tree["score"]