Fixed dynamic ONNX input

Fix dynamic ONNX input
Update docs with correct file name for tests

src/engines/engine_factory.pyx

@@ -1,3 +1,4 @@
+cimport constants_inf
 from loader_http_client cimport LoaderHttpClient, LoadResult
 
 
@@ -42,7 +43,6 @@ class EngineFactory:
 
     def build_and_cache(self, bytes source_bytes, LoaderHttpClient loader_client, str models_dir):
         cdef LoadResult res
-        import constants_inf
         engine_bytes, engine_filename = self.build_from_source(source_bytes, loader_client, models_dir)
         res = loader_client.upload_big_small_resource(engine_bytes, engine_filename, models_dir)
         if res.err is not None:
@@ -56,7 +56,6 @@ class OnnxEngineFactory(EngineFactory):
         return OnnxEngine(model_bytes)
 
     def get_source_filename(self):
-        import constants_inf
         return constants_inf.AI_ONNX_MODEL_FILE
 
 
@@ -81,7 +80,6 @@ class TensorRTEngineFactory(EngineFactory):
         return TensorRTEngine.get_engine_filename()
 
     def get_source_filename(self):
-        import constants_inf
         return constants_inf.AI_ONNX_MODEL_FILE
 
     def build_from_source(self, onnx_bytes, loader_client, models_dir):

src/engines/onnx_engine.pxd

@@ -8,6 +8,8 @@ cdef class OnnxEngine(InferenceEngine):
     cdef object model_inputs
     cdef str input_name
     cdef object input_shape
+    cdef object _resolved_input_hw
 
+    cdef tuple _resolve_input_hw(self, object metadata)
     cdef tuple get_input_shape(self)
     cdef run(self, input_data)

src/engines/onnx_engine.pyx

@@ -2,6 +2,7 @@ from engines.inference_engine cimport InferenceEngine
 import onnxruntime as onnx
 cimport constants_inf
 
+import ast
 import os
 
 def _select_providers():
@@ -29,15 +30,40 @@ cdef class OnnxEngine(InferenceEngine):
         model_meta = self.session.get_modelmeta()
         constants_inf.log(f"Metadata: {model_meta.custom_metadata_map}")
 
+        self._resolved_input_hw = self._resolve_input_hw(model_meta.custom_metadata_map)
+
         self._cpu_session = None
         if any("CoreML" in p for p in self.session.get_providers()):
             constants_inf.log(<str>'CoreML active — creating CPU fallback session')
             self._cpu_session = onnx.InferenceSession(
                 model_bytes, providers=["CPUExecutionProvider"])
 
+    cdef tuple _resolve_input_hw(self, object metadata):
+        cdef object h = self.input_shape[2] if len(self.input_shape) > 2 else None
+        cdef object w = self.input_shape[3] if len(self.input_shape) > 3 else None
+        cdef int resolved_h
+        cdef int resolved_w
+
+        if isinstance(h, int) and h > 0 and isinstance(w, int) and w > 0:
+            return <tuple>(h, w)
+
+        try:
+            imgsz = metadata.get("imgsz") if metadata is not None else None
+            if imgsz:
+                parsed = ast.literal_eval(imgsz)
+                if isinstance(parsed, (list, tuple)) and len(parsed) == 2:
+                    resolved_h = int(parsed[0])
+                    resolved_w = int(parsed[1])
+                    if resolved_h > 0 and resolved_w > 0:
+                        return <tuple>(resolved_h, resolved_w)
+        except Exception:
+            pass
+
+        # Dynamic ONNX models are expected to use the project's canonical 1280x1280 input.
+        return <tuple>(1280, 1280)
+
     cdef tuple get_input_shape(self):
-        shape = self.input_shape
-        return <tuple>(shape[2], shape[3])
+        return self._resolved_input_hw
 
     cdef run(self, input_data):
         try: