From 0ea955674a87eee1bd946a3a9673385c50a97844 Mon Sep 17 00:00:00 2001
From: Ox <co@dispension.ca>
Date: Mon, 21 Oct 2024 17:48:09 -0300
Subject: [PATCH] para test

---
 src/paravisionx.py | 50 ++++++++++++++++++++++++++++++++--------------
 1 file changed, 35 insertions(+), 15 deletions(-)

diff --git a/src/paravisionx.py b/src/paravisionx.py
index f61eecd19..9114fb663 100644
--- a/src/paravisionx.py
+++ b/src/paravisionx.py
@@ -3,7 +3,7 @@
 #
 import json
 import sys
-
+import numpy as np
 ### export PYTHONPATH=/wherever/yoloserv/modules ... as long as "paravision/.../" is in there
 from paravision.recognition.exceptions import ParavisionException
 from paravision.recognition.engine import Engine
@@ -47,31 +47,51 @@ class Paravision(FaceClass):
 
 
 
+
     # @doc compare two named images, previously loaded
     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[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 
+
+        # Debug: Print the encodings
         print(self.encs.keys())
         print(self.encs[name1])
         print(self.encs[name2])
+
         try:
+            # 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)
-            #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]
+            print("Match is ", res)
+
+            # Store the result in self.tree
+            self.tree["score"] = res  # Assuming 'res' is the match score
+
         except Exception as ex:
-            print("** paravision::compare exception ... " + str(ex) )
-            self.errstr =  "image comparison exception at compute_scores: "+str(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 success with the match score
+        return '{ "status":0, "remark":"OK", "score":%d }' % self.tree["score"]