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]"
+ ]
+ }
+ ]
  }
 ]