测试了一下rec模型的归一化参数

008测试PadleCOR_ONNX固定输入形状模型全流程.py

@@ -223,7 +223,10 @@ class PaddleOCRONNX:
         padded_image[:new_h, :new_w] = resized_image.astype(np.float32)
         
         # 归一化
-        padded_image = (padded_image / 255.0 - np.array([0.485, 0.456, 0.406], dtype=np.float32)) / np.array([0.229, 0.224, 0.225], dtype=np.float32)
+        # padded_image = (padded_image / 255.0 - np.array([0.485, 0.456, 0.406], dtype=np.float32)) / np.array([0.229, 0.224, 0.225], dtype=np.float32)
+        
+        # 不缩放反而会将识别结果再移后一个??
+        padded_image = (padded_image / 255.0).astype(np.float32)
         padded_image = padded_image.transpose((2, 0, 1)).astype(np.float32)
         
         return np.expand_dims(padded_image, axis=0).astype(np.float32)

009PaddleOCR_ONNX转rknn.py

@@ -16,7 +16,7 @@ rknn.config(
 )
 
 # 加载 ONNX, 只支持固定输入的onnx模型
-ret = rknn.load_onnx(model="/home/admin-root/haotian/康达瑞贝斯机器狗/rec_shape.onnx")
+ret = rknn.load_onnx(model="/home/admin-root/haotian/康达瑞贝斯机器狗/rec_shape_20250815.onnx")
 assert ret == 0, "加载 ONNX 失败！"
 
 # 转换模型
@@ -27,14 +27,15 @@ ret = rknn.build(
 assert ret == 0, "转换 RKNN 失败！"
 
 # 导出 RKNN
-ret = rknn.export_rknn("/home/admin-root/haotian/康达瑞贝斯机器狗/rec_shape.rknn")
+ret = rknn.export_rknn("/home/admin-root/haotian/康达瑞贝斯机器狗/rec_shape_20250815.rknn")
 assert ret == 0, "导出 RKNN 失败！"
 
 
 # Set inputs
 img = cv2.imread('/home/admin-root/haotian/rk3588/pytorch模型转rknn/images/bus.jpg')
 img = cv2.cvtColor(img, cv2.COLOR_BGR2RGB)
-img.resize((3, 640, 640))
+# img.resize((3, 640, 640))
+img.resize((3, 48, 320))
 img = np.expand_dims(img, 0)
 
 # Init runtime environment