AttributeError: type object 'Detections' has no attribute 'from_roboflow'. Did you mean: 'from_tensorflow'?

[yjseok]

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• I have searched the Supervision issues and found no similar bug report.

Bug

Hi,

I want to use "Use sahi" from the Code Snippets → Utilities section on the following page:
https://universe.roboflow.com/conedetection-6g6uc/cone-detection-6ltmn/model/3

from roboflow import Roboflow
import supervision as sv
import numpy as np
import cv2
import tempfile

image_path = "/home/vision01/sitevision/assets/emseong_data/image/cctv1.png"

rf = Roboflow(api_key="l4ccSLMANVHBmR0s1ywX")
project = rf.workspace().project("10k_cones")
model = project.version(1).model

def callback(image: np.ndarray) -> sv.Detections:
    with tempfile.NamedTemporaryFile(suffix=".jpg") as f:
        cv2.imwrite(f.name, image)
        result = model.predict(f.name, confidence=40, overlap=30).json()

    detections = sv.Detections.from_roboflow(result)
    return detections

image = cv2.imread(image_path)

slicer = sv.InferenceSlicer(callback=callback)

detections = slicer(image=image)

# add your classes from Roboflow, as they appear in the "Classes" section of the "Overview" tab of your model
classes = ["orange_cone"]

prediction_num = len(detections.xyxy)

box_annotator = sv.BoxAnnotator()

annotated_frame = box_annotator.annotate(
    scene=image.copy(),
    detections=detections,
    labels=[classes[detections.class_id[i]] for i in range(prediction_num)],
)

sv.plot_image(image=annotated_frame, size=(16, 16))

But I get the following error:
AttributeError: type object 'Detections' has no attribute 'from_roboflow'. Did you mean: 'from_tensorflow'?

How can I fix this?

Environment

No response

Minimal Reproducible Example

No response

Additional

No response

Are you willing to submit a PR?

• Yes I'd like to help by submitting a PR!

[specapoorv]

hi, can i work on this issue?

[specapoorv]

hi, simple fix for this issue was to replace method "from_roboflow" to "from_inference",
also you have to write all the classes
and there is no labels attribute in box_annotator.annotate function so i have commented it out

another issue is the output image has some bounding boxes scaling issues

from roboflow import Roboflow
import supervision as sv
import numpy as np
import cv2
import tempfile

rf = Roboflow(api_key="")
project = rf.workspace().project("cone-detection-6ltmn")
model = project.version(3).model

def callback(image: np.ndarray) -> sv.Detections:
    with tempfile.NamedTemporaryFile(suffix=".jpeg") as f:
        cv2.imwrite(f.name, image)

        result = model.predict(f.name, confidence=40, overlap=30).json()

        print("Original image shape:", image.shape)   # h, w, channels
        print("Roboflow processed image width:", result["image"]["width"])
        print("Roboflow processed image height:", result["image"]["height"])

    detections = sv.Detections.from_inference(result) #changed this: from_roboflow -> from_inference method

    return detections


image = cv2.imread("")
image = cv2.resize(image, (640, 640))

slicer = sv.InferenceSlicer(callback=callback)

detections = slicer(image=image)

# add your classes from Roboflow, as they appear in the "Classes" section of the "Overview" tab of your model
classes = ["blue", "blue_cone", "large_orange_cone", "orange", "orange_cone", "unknown_cone", "yellow"]
# added all classes here instead of only orange_cone

prediction_num = len(detections.xyxy)

box_annotator = sv.BoxAnnotator()

annotated_frame = box_annotator.annotate(
    scene=image.copy(),
    detections=detections,
    # labels=[classes[detections.class_id[i]] for i in range(prediction_num)],
)

sv.plot_image(image=annotated_frame)

I don't know how to update the snippet