Support trust_remote_code for pipeline and model (#1333)

2025-12-16 08:17:45 +01:00 · 2025-05-13 22:52:57 +08:00
parent c30bfeb777
commit 75d54927e1
18 changed files with 116 additions and 34 deletions
--- a/modelscope/models/base/base_model.py
+++ b/modelscope/models/base/base_model.py
@@ -30,10 +30,23 @@ class Model(ABC):
        device_name = kwargs.get('device', 'gpu')
        verify_device(device_name)
        self._device_name = device_name
+        self.trust_remote_code = kwargs.get('trust_remote_code', False)

    def __call__(self, *args, **kwargs) -> Dict[str, Any]:
        return self.postprocess(self.forward(*args, **kwargs))

+    def check_trust_remote_code(self, info_str: Optional[str] = None):
+        """Check trust_remote_code if the model needs to import extra libs
+
+        Args:
+            info_str(str): The info showed to user if trust_remote_code is `False`.
+        """
+        info_str = info_str or (
+            'This model requires `trust_remote_code` to be `True` because it needs to '
+            'import extra libs or execute the code in the model repo, setting this to true '
+            'means you trust the files in it.')
+        assert self.trust_remote_code, info_str
+
    @abstractmethod
    def forward(self, *args, **kwargs) -> Dict[str, Any]:
        """
--- a/modelscope/models/cv/anydoor/anydoor_model.py
+++ b/modelscope/models/cv/anydoor/anydoor_model.py
@@ -342,6 +342,8 @@ class ControlLDM(LatentDiffusion, Model):
        self.control_key = control_key
        self.only_mid_control = only_mid_control
        self.control_scales = [1.0] * 13
+        self.trust_remote_code = kwargs.get('trust_remote_code', False)
+        self.check_trust_remote_code()

    @torch.no_grad()
    def get_input(self, batch, k, bs=None, *args, **kwargs):
--- a/modelscope/models/cv/image_view_transform/image_view_transform_infer.py
+++ b/modelscope/models/cv/image_view_transform/image_view_transform_infer.py
@@ -68,6 +68,7 @@ class ImageViewTransform(TorchModel):
        self.model = None
        self.model = load_model_from_config(
            self.model, config, ckpt, device=self.device)
+        self.check_trust_remote_code()

    def forward(self, model_path, x, y):
        pred_results = _infer(self.model, model_path, x, y, self.device)
--- a/modelscope/models/cv/tinynas_detection/detector.py
+++ b/modelscope/models/cv/tinynas_detection/detector.py
@@ -29,7 +29,7 @@ class SingleStageDetector(TorchModel):
        init model by cfg
        """
        super().__init__(model_dir, *args, **kwargs)
-
+        self.check_trust_remote_code()
        config_path = osp.join(model_dir, self.config_name)
        config = parse_config(config_path)
        self.cfg = config
--- a/modelscope/models/cv/video_depth_estimation/dro_model.py
+++ b/modelscope/models/cv/video_depth_estimation/dro_model.py
@@ -33,6 +33,7 @@ class DROEstimation(TorchModel):
    def __init__(self, model_dir: str, **kwargs):
        """str -- model file root."""
        super().__init__(model_dir, **kwargs)
+        self.check_trust_remote_code()

        model_path = osp.join(model_dir, ModelFile.TORCH_MODEL_FILE)

--- a/modelscope/pipelines/audio/linear_aec_pipeline.py
+++ b/modelscope/pipelines/audio/linear_aec_pipeline.py
@@ -67,6 +67,10 @@ class LinearAECPipeline(Pipeline):
            model: model id on modelscope hub.
        """
        super().__init__(model=model, **kwargs)
+        self.check_trust_remote_code(
+            'This pipeline requires `trust_remote_code=True` to load the module defined'
+            ' in the `dey_mini.yaml`, setting this to True means you trust the code and files'
+            ' listed in this model repo.')

        self.use_cuda = torch.cuda.is_available()
        with open(
--- a/modelscope/pipelines/base.py
+++ b/modelscope/pipelines/base.py
@@ -7,7 +7,7 @@ from abc import ABC, abstractmethod
 from functools import partial
 from multiprocessing import Pool
 from threading import Lock
-from typing import Any, Dict, Generator, List, Mapping, Union
+from typing import Any, Dict, Generator, List, Mapping, Optional, Union

 import numpy as np
 from packaging import version
@@ -45,6 +45,8 @@ class Pipeline(ABC):
    """

    def initiate_single_model(self, model, **kwargs):
+        if self.trust_remote_code:
+            kwargs['trust_remote_code'] = True
        if isinstance(model, str):
            logger.info(f'initiate model from {model}')
        if isinstance(model, str) and is_official_hub_path(model):
@@ -95,6 +97,7 @@ class Pipeline(ABC):
        self.device_map = device_map
        verify_device(device)
        self.device_name = device
+        self.trust_remote_code = kwargs.get('trust_remote_code', False)

        if not isinstance(model, List):
            self.model = self.initiate_single_model(model, **kwargs)
@@ -133,6 +136,18 @@ class Pipeline(ABC):
        self._compile = kwargs.get('compile', False)
        self._compile_options = kwargs.get('compile_options', {})

+    def check_trust_remote_code(self, info_str: Optional[str] = None):
+        """Check trust_remote_code if the pipeline needs to import extra libs
+
+        Args:
+            info_str(str): The info showed to user if trust_remote_code is `False`.
+        """
+        info_str = info_str or (
+            'This pipeline requires `trust_remote_code` to be `True` because it needs to '
+            'import extra libs or execute the code in the model repo, setting this to true '
+            'means you trust the files in it.')
+        assert self.trust_remote_code, info_str
+
    def prepare_model(self):
        """ Place model on certain device for pytorch models before first inference
        """
--- a/modelscope/pipelines/cv/pedestrian_attribute_recognition_pipeline.py
+++ b/modelscope/pipelines/cv/pedestrian_attribute_recognition_pipeline.py
@@ -63,7 +63,8 @@ class PedestrainAttributeRecognitionPipeline(Pipeline):
        self.human_detect_model_id = 'damo/cv_tinynas_human-detection_damoyolo'
        self.human_detector = pipeline(
            Tasks.domain_specific_object_detection,
-            model=self.human_detect_model_id)
+            model=self.human_detect_model_id,
+            trust_remote_code=kwargs.get('trust_remote_code', False))

    def get_labels(self, outputs, thres=0.5):
        gender = outputs[0][0:1]
--- a/modelscope/pipelines/multi_modal/disco_guided_diffusion_pipeline/disco_guided_diffusion.py
+++ b/modelscope/pipelines/multi_modal/disco_guided_diffusion_pipeline/disco_guided_diffusion.py
@@ -189,6 +189,11 @@ class DiscoDiffusionPipeline(DiffusersPipeline):
        """

        super().__init__(model, device, **kwargs)
+        self.trust_remote_code = kwargs.get('trust_remote_code', False)
+        self.check_trust_remote_code(
+            'This pipeline requires `trust_remote_code=True` to load the module defined'
+            ' in `model_index.json`, setting this to True means you trust the code and files'
+            ' listed in this model repo.')

        model_path = model

@@ -204,6 +209,12 @@ class DiscoDiffusionPipeline(DiffusersPipeline):
        if model_config['use_fp16']:
            self.unet.convert_to_fp16()

+        self.trust_remote_code = kwargs.get('trust_remote_code', False)
+        self.check_trust_remote_code(
+            'This pipeline requires import modules listed in `model_index.json`, '
+            'please add `trust_remote_code=True` if you trust this model repo.'
+        )
+
        with open(
                os.path.join(model_path, 'model_index.json'),
                'r',
--- a/tests/export/test_export_object_detection_damoyolo.py
+++ b/tests/export/test_export_object_detection_damoyolo.py
@@ -23,7 +23,7 @@ class TestExportObjectDetectionDamoyolo(unittest.TestCase):
    @unittest.skipUnless(test_level() >= 0, 'skip test in current test level')
    def test_export_object_detection_damoyolo(self):

-        model = Model.from_pretrained(self.model_id)
+        model = Model.from_pretrained(self.model_id, trust_remote_code=True)
        Exporter.from_model(model).export_onnx(
            input_shape=(1, 3, 640, 640), output_dir=self.tmp_dir)

@@ -31,7 +31,7 @@ class TestExportObjectDetectionDamoyolo(unittest.TestCase):
    def test_export_domain_specific_object_detection_damoyolo(self):

        model_id = 'damo/cv_tinynas_human-detection_damoyolo'
-        model = Model.from_pretrained(model_id)
+        model = Model.from_pretrained(model_id, trust_remote_code=True)
        with tempfile.TemporaryDirectory() as tmp_dir:
            Exporter.from_model(model).export_onnx(
                input_shape=(1, 3, 640, 640), output_dir=tmp_dir)
--- a/tests/pipelines/test_anydoor.py
+++ b/tests/pipelines/test_anydoor.py
@@ -22,7 +22,7 @@ class AnydoorTest(unittest.TestCase):
        save_path = 'data/test/images/image_anydoor_gen.png'

        anydoor_pipline: AnydoorPipeline = pipeline(
-            self.task, model=self.model_id)
+            self.task, model=self.model_id, trust_remote_code=True)
        out = anydoor_pipline((ref_image, ref_mask, bg_image, bg_mask))
        image = out['output_img']
        image.save(save_path)
--- a/tests/pipelines/test_disco_guided_diffusion.py
+++ b/tests/pipelines/test_disco_guided_diffusion.py
@@ -21,7 +21,10 @@ class DiscoGuidedDiffusionTest(unittest.TestCase):
    @unittest.skipUnless(test_level() >= 0, 'skip test in current test level')
    def test_run(self):
        diffusers_pipeline = pipeline(
-            task=self.task, model=self.model_id1, model_revision='v1.0')
+            task=self.task,
+            model=self.model_id1,
+            model_revision='v1.0',
+            trust_remote_code=True)
        output = diffusers_pipeline({
            'text': self.test_input1,
            'height': 256,
@@ -31,7 +34,10 @@ class DiscoGuidedDiffusionTest(unittest.TestCase):
        print('Image saved to output1.png')

        diffusers_pipeline = pipeline(
-            task=self.task, model=self.model_id2, model_revision='v1.0')
+            task=self.task,
+            model=self.model_id2,
+            model_revision='v1.0',
+            trust_remote_code=True)
        output = diffusers_pipeline({
            'text': self.test_input2,
            'height': 256,
--- a/tests/pipelines/test_image_control_3d_portrait.py
+++ b/tests/pipelines/test_image_control_3d_portrait.py
@@ -16,7 +16,7 @@ class ImageControl3dPortraitTest(unittest.TestCase):

    def setUp(self) -> None:
        self.model_id = 'damo/cv_vit_image-control-3d-portrait-synthesis'
-        self.test_image = 'data/test/images/image_control_3d_portrait.jpg'
+        self.test_image = '/mnt/nas3/yzhao/1.jpg'
        self.save_dir = 'exp'
        os.makedirs(self.save_dir, exist_ok=True)

--- a/tests/pipelines/test_image_view_transform.py
+++ b/tests/pipelines/test_image_view_transform.py
@@ -36,12 +36,16 @@ class ImageViewTransformTest(unittest.TestCase):
    @unittest.skipUnless(test_level() >= 0, 'skip test in current test level')
    def test_run_modelhub(self):
        image_view_transform = pipeline(
-            Tasks.image_view_transform, model=self.model_id, revision='v1.0.3')
+            Tasks.image_view_transform,
+            model=self.model_id,
+            revision='v1.0.3',
+            trust_remote_code=True)
        self.pipeline_inference(image_view_transform, self.input)

    @unittest.skipUnless(test_level() >= 2, 'skip test in current test level')
    def test_run_modelhub_default_model(self):
-        image_view_transform = pipeline(Tasks.image_view_transform)
+        image_view_transform = pipeline(
+            Tasks.image_view_transform, trust_remote_code=True)
        self.pipeline_inference(image_view_transform, self.input)


--- a/tests/pipelines/test_pedestrian_attribute_recognition.py
+++ b/tests/pipelines/test_pedestrian_attribute_recognition.py
@@ -26,14 +26,14 @@ class PedestrianAttributeRecognitionTest(unittest.TestCase):
    @unittest.skipUnless(test_level() >= 0, 'skip test in current test level')
    def test_run_modelhub_with_image_file(self):
        pedestrian_attribute_recognition = pipeline(
-            self.task, model=self.model_id)
+            self.task, model=self.model_id, trust_remote_code=True)
        self.pipeline_inference(pedestrian_attribute_recognition,
                                self.test_image)

    @unittest.skipUnless(test_level() >= 0, 'skip test in current test level')
    def test_run_modelhub_with_image_input(self):
        pedestrian_attribute_recognition = pipeline(
-            self.task, model=self.model_id)
+            self.task, model=self.model_id, trust_remote_code=True)
        self.pipeline_inference(pedestrian_attribute_recognition,
                                Image.open(self.test_image))

--- a/tests/pipelines/test_tinynas_detection.py
+++ b/tests/pipelines/test_tinynas_detection.py
@@ -19,7 +19,9 @@ class TinynasObjectDetectionTest(unittest.TestCase):
    @unittest.skipUnless(test_level() >= 0, 'skip test in current test level')
    def test_run_airdet(self):
        tinynas_object_detection = pipeline(
-            Tasks.image_object_detection, model='damo/cv_tinynas_detection')
+            Tasks.image_object_detection,
+            model='damo/cv_tinynas_detection',
+            trust_remote_code=True)
        result = tinynas_object_detection(
            'data/test/images/image_detection.jpg')
        print('airdet', result)
@@ -28,7 +30,8 @@ class TinynasObjectDetectionTest(unittest.TestCase):
    def test_run_damoyolo(self):
        tinynas_object_detection = pipeline(
            Tasks.image_object_detection,
-            model='damo/cv_tinynas_object-detection_damoyolo')
+            model='damo/cv_tinynas_object-detection_damoyolo',
+            trust_remote_code=True)
        result = tinynas_object_detection(
            'data/test/images/image_detection.jpg')
        print('damoyolo-s', result)
@@ -37,7 +40,8 @@ class TinynasObjectDetectionTest(unittest.TestCase):
    def test_run_damoyolo_m(self):
        tinynas_object_detection = pipeline(
            Tasks.image_object_detection,
-            model='damo/cv_tinynas_object-detection_damoyolo-m')
+            model='damo/cv_tinynas_object-detection_damoyolo-m',
+            trust_remote_code=True)
        result = tinynas_object_detection(
            'data/test/images/image_detection.jpg')
        print('damoyolo-m', result)
@@ -46,7 +50,8 @@ class TinynasObjectDetectionTest(unittest.TestCase):
    def test_run_damoyolo_t(self):
        tinynas_object_detection = pipeline(
            Tasks.image_object_detection,
-            model='damo/cv_tinynas_object-detection_damoyolo-t')
+            model='damo/cv_tinynas_object-detection_damoyolo-t',
+            trust_remote_code=True)
        result = tinynas_object_detection(
            'data/test/images/image_detection.jpg')
        print('damoyolo-t', result)
@@ -56,7 +61,8 @@ class TinynasObjectDetectionTest(unittest.TestCase):
        test_image = 'data/test/images/image_detection.jpg'
        tinynas_object_detection = pipeline(
            Tasks.image_object_detection,
-            model='damo/cv_tinynas_object-detection_damoyolo-m')
+            model='damo/cv_tinynas_object-detection_damoyolo-m',
+            trust_remote_code=True)
        result = tinynas_object_detection(test_image)
        tinynas_object_detection.show_result(test_image, result,
                                             'demo_ret.jpg')
@@ -65,7 +71,8 @@ class TinynasObjectDetectionTest(unittest.TestCase):
    def test_human_detection_damoyolo(self):
        tinynas_object_detection = pipeline(
            Tasks.domain_specific_object_detection,
-            model='damo/cv_tinynas_human-detection_damoyolo')
+            model='damo/cv_tinynas_human-detection_damoyolo',
+            trust_remote_code=True)
        result = tinynas_object_detection(
            'data/test/images/image_detection.jpg')
        assert result and (OutputKeys.SCORES in result) and (
@@ -76,7 +83,8 @@ class TinynasObjectDetectionTest(unittest.TestCase):
    def test_human_detection_damoyolo_with_image(self):
        tinynas_object_detection = pipeline(
            Tasks.domain_specific_object_detection,
-            model='damo/cv_tinynas_human-detection_damoyolo')
+            model='damo/cv_tinynas_human-detection_damoyolo',
+            trust_remote_code=True)
        img = Image.open('data/test/images/image_detection.jpg')
        result = tinynas_object_detection(img)
        assert result and (OutputKeys.SCORES in result) and (
@@ -87,7 +95,8 @@ class TinynasObjectDetectionTest(unittest.TestCase):
    def test_facemask_detection_damoyolo(self):
        tinynas_object_detection = pipeline(
            Tasks.domain_specific_object_detection,
-            model='damo/cv_tinynas_object-detection_damoyolo_facemask')
+            model='damo/cv_tinynas_object-detection_damoyolo_facemask',
+            trust_remote_code=True)
        result = tinynas_object_detection(
            'data/test/images/image_detection.jpg')
        assert result and (OutputKeys.SCORES in result) and (
@@ -98,7 +107,8 @@ class TinynasObjectDetectionTest(unittest.TestCase):
    def test_facemask_detection_damoyolo_with_image(self):
        tinynas_object_detection = pipeline(
            Tasks.domain_specific_object_detection,
-            model='damo/cv_tinynas_object-detection_damoyolo_facemask')
+            model='damo/cv_tinynas_object-detection_damoyolo_facemask',
+            trust_remote_code=True)
        img = Image.open('data/test/images/image_detection.jpg')
        result = tinynas_object_detection(img)
        assert result and (OutputKeys.SCORES in result) and (
@@ -109,7 +119,8 @@ class TinynasObjectDetectionTest(unittest.TestCase):
    def test_safetyhat_detection_damoyolo(self):
        tinynas_object_detection = pipeline(
            Tasks.domain_specific_object_detection,
-            model='damo/cv_tinynas_object-detection_damoyolo_safety-helmet')
+            model='damo/cv_tinynas_object-detection_damoyolo_safety-helmet',
+            trust_remote_code=True)
        result = tinynas_object_detection(
            'data/test/images/image_safetyhat.jpg')
        assert result and (OutputKeys.SCORES in result) and (
@@ -120,7 +131,8 @@ class TinynasObjectDetectionTest(unittest.TestCase):
    def test_safetyhat_detection_damoyolo_with_image(self):
        tinynas_object_detection = pipeline(
            Tasks.domain_specific_object_detection,
-            model='damo/cv_tinynas_object-detection_damoyolo_safety-helmet')
+            model='damo/cv_tinynas_object-detection_damoyolo_safety-helmet',
+            trust_remote_code=True)
        img = Image.open('data/test/images/image_safetyhat.jpg')
        result = tinynas_object_detection(img)
        assert result and (OutputKeys.SCORES in result) and (
@@ -131,7 +143,8 @@ class TinynasObjectDetectionTest(unittest.TestCase):
    def test_cigarette_detection_damoyolo(self):
        tinynas_object_detection = pipeline(
            Tasks.domain_specific_object_detection,
-            model='damo/cv_tinynas_object-detection_damoyolo_cigarette')
+            model='damo/cv_tinynas_object-detection_damoyolo_cigarette',
+            trust_remote_code=True)
        result = tinynas_object_detection('data/test/images/image_smoke.jpg')
        assert result and (OutputKeys.SCORES in result) and (
            OutputKeys.LABELS in result) and (OutputKeys.BOXES in result)
@@ -141,7 +154,8 @@ class TinynasObjectDetectionTest(unittest.TestCase):
    def test_cigarette_detection_damoyolo_with_image(self):
        tinynas_object_detection = pipeline(
            Tasks.domain_specific_object_detection,
-            model='damo/cv_tinynas_object-detection_damoyolo_cigarette')
+            model='damo/cv_tinynas_object-detection_damoyolo_cigarette',
+            trust_remote_code=True)
        img = Image.open('data/test/images/image_smoke.jpg')
        result = tinynas_object_detection(img)
        assert result and (OutputKeys.SCORES in result) and (
@@ -152,7 +166,8 @@ class TinynasObjectDetectionTest(unittest.TestCase):
    def test_phone_detection_damoyolo(self):
        tinynas_object_detection = pipeline(
            Tasks.domain_specific_object_detection,
-            model='damo/cv_tinynas_object-detection_damoyolo_phone')
+            model='damo/cv_tinynas_object-detection_damoyolo_phone',
+            trust_remote_code=True)
        result = tinynas_object_detection('data/test/images/image_phone.jpg')
        assert result and (OutputKeys.SCORES in result) and (
            OutputKeys.LABELS in result) and (OutputKeys.BOXES in result)
@@ -162,7 +177,8 @@ class TinynasObjectDetectionTest(unittest.TestCase):
    def test_phone_detection_damoyolo_with_image(self):
        tinynas_object_detection = pipeline(
            Tasks.domain_specific_object_detection,
-            model='damo/cv_tinynas_object-detection_damoyolo_phone')
+            model='damo/cv_tinynas_object-detection_damoyolo_phone',
+            trust_remote_code=True)
        img = Image.open('data/test/images/image_phone.jpg')
        result = tinynas_object_detection(img)
        assert result and (OutputKeys.SCORES in result) and (
@@ -173,7 +189,8 @@ class TinynasObjectDetectionTest(unittest.TestCase):
    def test_head_detection_damoyolo(self):
        tinynas_object_detection = pipeline(
            Tasks.domain_specific_object_detection,
-            model='damo/cv_tinynas_head-detection_damoyolo')
+            model='damo/cv_tinynas_head-detection_damoyolo',
+            trust_remote_code=True)
        result = tinynas_object_detection(
            'data/test/images/image_detection.jpg')
        assert result and (OutputKeys.SCORES in result) and (
@@ -184,7 +201,8 @@ class TinynasObjectDetectionTest(unittest.TestCase):
    def test_head_detection_damoyolo_with_image(self):
        tinynas_object_detection = pipeline(
            Tasks.domain_specific_object_detection,
-            model='damo/cv_tinynas_head-detection_damoyolo')
+            model='damo/cv_tinynas_head-detection_damoyolo',
+            trust_remote_code=True)
        img = Image.open('data/test/images/image_detection.jpg')
        result = tinynas_object_detection(img)
        assert result and (OutputKeys.SCORES in result) and (
@@ -195,7 +213,8 @@ class TinynasObjectDetectionTest(unittest.TestCase):
    def test_smokefire_detection_damoyolo(self):
        tinynas_object_detection = pipeline(
            Tasks.domain_specific_object_detection,
-            model='damo/cv_tinynas_object-detection_damoyolo_smokefire')
+            model='damo/cv_tinynas_object-detection_damoyolo_smokefire',
+            trust_remote_code=True)
        result = tinynas_object_detection(
            'data/test/images/image_smokefire_detection.jpg')
        assert result and (OutputKeys.SCORES in result) and (
@@ -206,7 +225,8 @@ class TinynasObjectDetectionTest(unittest.TestCase):
    def test_smokefire_detection_damoyolo_with_image(self):
        tinynas_object_detection = pipeline(
            Tasks.domain_specific_object_detection,
-            model='damo/cv_tinynas_object-detection_damoyolo_smokefire')
+            model='damo/cv_tinynas_object-detection_damoyolo_smokefire',
+            trust_remote_code=True)
        img = Image.open('data/test/images/image_smokefire_detection.jpg')
        result = tinynas_object_detection(img)
        assert result and (OutputKeys.SCORES in result) and (
--- a/tests/pipelines/test_traffic_sign_detection.py
+++ b/tests/pipelines/test_traffic_sign_detection.py
@@ -20,7 +20,8 @@ class TrafficSignDetectionTest(unittest.TestCase):
    def test_traffic_sign_detection_damoyolo(self):
        tinynas_object_detection = pipeline(
            Tasks.domain_specific_object_detection,
-            model='damo/cv_tinynas_object-detection_damoyolo_traffic_sign')
+            model='damo/cv_tinynas_object-detection_damoyolo_traffic_sign',
+            trust_remote_code=True)
        result = tinynas_object_detection(
            'data/test/images/image_traffic_sign.jpg')
        assert result and (OutputKeys.SCORES in result) and (
--- a/tests/pipelines/test_video_depth_estimation.py
+++ b/tests/pipelines/test_video_depth_estimation.py
@@ -17,7 +17,10 @@ class VideoDepthEstimationTest(unittest.TestCase):
    @unittest.skipUnless(test_level() >= 0, 'skip test in current test level')
    def test_video_depth_estimation(self):
        input_location = 'data/test/videos/video_depth_estimation.mp4'
-        estimator = pipeline(Tasks.video_depth_estimation, model=self.model_id)
+        estimator = pipeline(
+            Tasks.video_depth_estimation,
+            model=self.model_id,
+            trust_remote_code=True)
        result = estimator(input_location)
        show_video_depth_estimation_result(result[OutputKeys.DEPTHS_COLOR],
                                           'out.mp4')