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fix: make SAM 2 work in case data value is a list of images #835

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fix: make SAM 2 work in case data value is a list of images #835

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20 changes: 16 additions & 4 deletions label_studio_ml/examples/segment_anything_2_image/model.py
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Original file line number Diff line number Diff line change
Expand Up @@ -43,7 +43,7 @@ class NewModel(LabelStudioMLBase):
"""Custom ML Backend model
"""

def get_results(self, masks, probs, width, height, from_name, to_name, label):
def get_results(self, masks, probs, width, height, from_name, to_name, label, item_index):
results = []
total_prob = 0
for mask, prob in zip(masks, probs):
Expand All @@ -53,7 +53,7 @@ def get_results(self, masks, probs, width, height, from_name, to_name, label):
mask = mask * 255
rle = brush.mask2rle(mask)
total_prob += prob
results.append({
annotation_result = {
'id': label_id,
'from_name': from_name,
'to_name': to_name,
Expand All @@ -68,7 +68,13 @@ def get_results(self, masks, probs, width, height, from_name, to_name, label):
'score': prob,
'type': 'brushlabels',
'readonly': False
})
}


if item_index is not None:
annotation_result['item_index'] = item_index

results.append(annotation_result)

return [{
'result': results,
Expand Down Expand Up @@ -139,6 +145,11 @@ def predict(self, tasks: List[Dict], context: Optional[Dict] = None, **kwargs) -
print(f'Point coords are {point_coords}, point labels are {point_labels}, input box is {input_box}')

img_url = tasks[0]['data'][value]
if isinstance(img_url, list):
item_index = context['result'][0]['item_index']
img_url = img_url[item_index]
else:
item_index = None
predictor_results = self._sam_predict(
img_url=img_url,
point_coords=point_coords or None,
Expand All @@ -154,6 +165,7 @@ def predict(self, tasks: List[Dict], context: Optional[Dict] = None, **kwargs) -
height=image_height,
from_name=from_name,
to_name=to_name,
label=selected_label)
label=selected_label,
item_index=item_index)

return ModelResponse(predictions=predictions)