fix: GETI-422 ssd dynamic model with prepropcessing fix (#430)

* fix

* tests

Author: mgumowsk

src/model_api/models/image_model.py

@@ -220,23 +220,32 @@ def preprocess(self, inputs: np.ndarray) -> list[dict]:
                 }
             - the input metadata, which might be used in `postprocess` method
         """
-        if self._is_dynamic:
+        original_shape = inputs.shape
+
+        if self.embedded_processing:
+            processed_image = inputs[None]
+            if self._is_dynamic:
+                h, w, c = inputs.shape
+                resized_shape = (w, h, c)
+            else:
+                resized_shape = (self.w, self.h, self.c)
+        elif self._is_dynamic:
             h, w, c = inputs.shape
             resized_shape = (w, h, c)
             processed_image = self.input_transform(inputs)
             processed_image = self._change_layout(processed_image)
         else:
+            # Fixed model without embedded preprocessing
             resized_shape = (self.w, self.h, self.c)
-            if self.embedded_processing:
-                processed_image = inputs[None]
-            else:
-                processed_image = self.input_transform(inputs)
-                processed_image = self._change_layout(processed_image)
+
+            resized_image = self.resize(inputs, (self.w, self.h), pad_value=self.pad_value)
+            processed_image = self.input_transform(resized_image)
+            processed_image = self._change_layout(processed_image)
 
         return [
             {self.image_blob_name: processed_image},
             {
-                "original_shape": inputs.shape,
+                "original_shape": original_shape,
                 "resized_shape": resized_shape,
             },
         ]

tests/accuracy/images.json

@@ -19,5 +19,8 @@
   },
   {
     "name": "images/Slide4.PNG"
+  },
+  {
+    "name": "images/cards.png"
   }
 ]

tests/accuracy/prepare_data.py

@@ -11,17 +11,28 @@
 import httpx
 
 
+async def download_single_image(client, url, filename):
+    image = await client.get(url)
+    with Path(filename).open("wb") as im:
+        im.write(image.content)
+
+
 async def download_images(data_dir):
     async with httpx.AsyncClient(timeout=20.0) as client:
-        COCO128_URL = "https://ultralytics.com/assets/coco128.zip"
+        COCO128_URL = "https://storage.geti.intel.com/geti_predict/test/images/coco128.zip"
         archive = await client.get(COCO128_URL, follow_redirects=True)
         with ZipFile(BytesIO(archive.content)) as zfile:
             zfile.extractall(data_dir)
-        image = await client.get(
-            "https://raw.githubusercontent.com/Shenggan/BCCD_Dataset/master/BCCD/JPEGImages/BloodImage_00007.jpg",
-        )
-        with Path(data_dir / "BloodImage_00007.jpg").open("wb") as im:
-            im.write(image.content)
+
+        image_downloads = [
+            (
+                "https://storage.geti.intel.com/geti_predict/test/images/BloodImage_00007.jpg",
+                data_dir / "BloodImage_00007.jpg",
+            ),
+            ("https://storage.geti.intel.com/geti_predict/test/images/cards.png", data_dir / "cards.png"),
+        ]
+
+        await asyncio.gather(*[download_single_image(client, url, filename) for url, filename in image_downloads])
 
 
 async def stream_file(client, url, filename):
@@ -155,6 +166,7 @@ async def main():
             download_otx_model(client, otx_models_dir, "sam_vit_b_zsl_decoder"),
             download_otx_model(client, otx_models_dir, "rtmpose_tiny"),
             download_otx_model(client, otx_models_dir, "segnext_t_tiling"),
+            download_otx_model(client, otx_models_dir, "ssd-card-detection"),
             download_anomalib_model(client, anomalib_models_dir, "padim"),
             download_anomalib_model(client, anomalib_models_dir, "stfpm"),
             download_anomalib_model(client, anomalib_models_dir, "uflow"),

tests/accuracy/public_scope.json

@@ -477,5 +477,17 @@
         ]
       }
     ]
+  },
+  {
+    "name": "otx_models/ssd-card-detection.xml",
+    "type": "DetectionModel",
+    "test_data": [
+      {
+        "image": "coco128/images/train2017/000000000074.jpg",
+        "reference": [
+          "79, 281, 318, 371, 1 (Diamonds): 0.700; 0, 75, 172, 333, 1 (Diamonds): 0.575; 109, 6, 625, 224, 3 (Hearts): 0.547; [0]; [0]"
+        ]
+      }
+    ]
   }
 ]