Require paddlepaddle>=3.0.0 with new `*.pdiparams (#13552)

export.py

@@ -510,7 +510,7 @@ def export_paddle(model, im, file, metadata, prefix=colorstr("PaddlePaddle:")):
         $ pip install paddlepaddle x2paddle
         ```
     """
-    check_requirements(("paddlepaddle<3.0.0", "x2paddle"))
+    check_requirements(("paddlepaddle>=3.0.0", "x2paddle"))
     import x2paddle
     from x2paddle.convert import pytorch2paddle
 

models/common.py

@@ -644,20 +644,32 @@ class DetectMultiBackend(nn.Module):
                     stride, names = int(meta["stride"]), meta["names"]
         elif tfjs:  # TF.js
             raise NotImplementedError("ERROR: YOLOv5 TF.js inference is not supported")
-        elif paddle:  # PaddlePaddle
+        # PaddlePaddle
+        elif paddle:
             LOGGER.info(f"Loading {w} for PaddlePaddle inference...")
-            check_requirements("paddlepaddle-gpu" if cuda else "paddlepaddle<3.0.0")
+            check_requirements("paddlepaddle-gpu" if cuda else "paddlepaddle>=3.0.0")
             import paddle.inference as pdi
 
-            if not Path(w).is_file():  # if not *.pdmodel
+            w = Path(w)
-                w = next(Path(w).rglob("*.pdmodel"))  # get *.pdmodel file from *_paddle_model dir
+            if w.is_dir():
-            weights = Path(w).with_suffix(".pdiparams")
+                model_file = next(w.rglob("*.json"), None)
-            config = pdi.Config(str(w), str(weights))
+                params_file = next(w.rglob("*.pdiparams"), None)
+            elif w.suffix == ".pdiparams":
+                model_file = w.with_name("model.json")
+                params_file = w
+            else:
+                raise ValueError(f"Invalid model path {w}. Provide model directory or a .pdiparams file.")
+
+            if not (model_file and params_file and model_file.is_file() and params_file.is_file()):
+                raise FileNotFoundError(f"Model files not found in {w}. Both .json and .pdiparams files are required.")
+
+            config = pdi.Config(str(model_file), str(params_file))
             if cuda:
                 config.enable_use_gpu(memory_pool_init_size_mb=2048, device_id=0)
             predictor = pdi.create_predictor(config)
             input_handle = predictor.get_input_handle(predictor.get_input_names()[0])
             output_names = predictor.get_output_names()
+
         elif triton:  # NVIDIA Triton Inference Server
             LOGGER.info(f"Using {w} as Triton Inference Server...")
             check_requirements("tritonclient[all]")