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ultralytics/engine/exporter.py

@@ -247,7 +247,9 @@ class Exporter:
             assert not getattr(model, "end2end", False), "TFLite INT8 export not supported for end2end models."
         if edgetpu or imx500:
             if not LINUX:
-                raise SystemError("Edge TPU (https://coral.ai/docs/edgetpu/compiler) and IMX500 (https://developer.aitrios.sony-semicon.com/en/raspberrypi-ai-camera/documentation/imx500-converter) export only supported on Linux.")
+                raise SystemError(
+                    "Edge TPU (https://coral.ai/docs/edgetpu/compiler) and IMX500 (https://developer.aitrios.sony-semicon.com/en/raspberrypi-ai-camera/documentation/imx500-converter) export only supported on Linux."
+                )
             elif self.args.batch != 1:  # see github.com/ultralytics/ultralytics/pull/13420
                 LOGGER.warning("WARNING ⚠️ Edge TPU export requires batch size 1, setting batch=1.")
                 self.args.batch = 1
@@ -1113,16 +1115,19 @@ class Exporter:
             raise ValueError("IMX500 export is only supported for YOLOv8 detection models")
         check_requirements(("model-compression-toolkit==2.1.1", "sony-custom-layers==0.2.0", "tensorflow==2.12.0"))
         check_requirements("imx500-converter[pt]==3.14.3")
-        
+
+        import subprocess
+
         import model_compression_toolkit as mct
         import onnx
-        import subprocess
         from sony_custom_layers.pytorch.object_detection.nms import multiclass_nms
-        
+
         try:
             subprocess.run(["java", "--version"], check=True)
-        except EnvironmentError:
-            raise EnvironmentError("Java 17 is required for the imx500 conversion. \n Please install Java with: \n sudo apt install openjdk-17-jdk openjdk-17-jre")
+        except OSError:
+            raise OSError(
+                "Java 17 is required for the imx500 conversion. \n Please install Java with: \n sudo apt install openjdk-17-jdk openjdk-17-jre"
+            )
 
         def representative_dataset_gen(dataloader=self.get_int8_calibration_dataloader(prefix)):
             for batch in dataloader:
@@ -1214,10 +1219,13 @@ class Exporter:
             meta.key, meta.value = k, str(v)
 
         onnx.save(model_onnx, f)
-                
+
         output_dir = Path(str(self.file).replace(self.file.suffix, "_imx500_model"))
 
-        subprocess.run(["imxconv-pt", "-i", str(f), "-o", str(output_dir), "--no-input-persistency", "--overwrite-output"], check=True)
+        subprocess.run(
+            ["imxconv-pt", "-i", str(f), "-o", str(output_dir), "--no-input-persistency", "--overwrite-output"],
+            check=True,
+        )
 
         with open(output_dir / "labels.txt", "w") as file:
             file.writelines([f"{name}\n" for _, name in self.model.names.items()])