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|---|---|---|---|---|---|---|---|
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1,006 | 1,280 | 720 | {
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1,027 | 340 | 736 | {
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1,011 | 1,920 | 1,088 | {
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1,022 | 800 | 450 | {
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1,024 | 1,440 | 810 | {
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... | <ref>Coverall</ref><box><170><0><821><1000></box>, <ref>Face Shield</ref><box><333><195><731><948></box>, <ref>Gloves</ref><box>none</box>, <ref>Goggles</ref><box><403><396><670><576></box>, <ref>Mask</ref><box><421><485><671><930></box> | {"model_id": "tencent/WeVisOne-VL-4B", "prompt": "Locate all the instances that match the following description: Coverall. Face Shield. Gloves. Goggles. Mask.", "classes": ["Coverall", "Face_Shield", "Gloves", "Goggles", "Mask"], "image_size": [1440, 810], "min_pixels": 16384, "max_pixels": 2073600, "duplicate_iou": 0.... | |
1,025 | 2,000 | 2,000 | {
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1,003 | 1,920 | 1,088 | {
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1,021 | 626 | 417 | {
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1,010 | 1,920 | 1,088 | {
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1,009 | 750 | 500 | {
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1,002 | 1,280 | 720 | {
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1,013 | 1,920 | 1,088 | {
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"area": [
63240,
81571,
175978
],
"bbox": [
[
359,
214,
340,
186
],
[
357,
287,
301,
271
],
[
299,
127,
421,
418
]
],
"category": [
3,
4,
1
]
} | [
{
"bbox": [
84,
0,
850,
576
],
"label": "Coverall",
"sub_label": "",
"alt_labels": []
},
{
"bbox": [
313,
175,
707,
559
],
"label": "Face_Shield",
"sub_label": "",
"alt_labels": []
},
{
"bbox": [
304,
130... | <ref>Coverall</ref><box><82><0><830><1000></box>, <ref>Face Shield</ref><box><306><304><690><970></box>, <ref>Gloves</ref><box>none</box>, <ref>Goggles</ref><box><297><225><702><519></box>, <ref>Mask</ref><box><348><498><642><965></box> | {"model_id": "tencent/WeVisOne-VL-4B", "prompt": "Locate all the instances that match the following description: Coverall. Face Shield. Gloves. Goggles. Mask.", "classes": ["Coverall", "Face_Shield", "Gloves", "Goggles", "Mask"], "image_size": [1024, 576], "min_pixels": 16384, "max_pixels": 2073600, "duplicate_iou": 0.... | |
1,029 | 1,200 | 800 | {
"id": [
198,
199,
200,
201,
202,
203,
204,
205,
206,
207
],
"area": [
4840,
4488,
13915,
5628,
5850,
4830,
9393,
4081,
178024,
294320
],
"bbox": [
[
721,
326,
110,
44
],
[
395,
78,... | [
{
"bbox": [
356,
0,
734,
628
],
"label": "Coverall",
"sub_label": "",
"alt_labels": []
},
{
"bbox": [
542,
229,
1062,
800
],
"label": "Coverall",
"sub_label": "",
"alt_labels": []
},
{
"bbox": [
379,
0,
... | <ref>Coverall</ref><box><297><0><612><785>,<452><286><885><1000></box>, <ref>Face Shield</ref><box><316><0><465><148></box>, <ref>Gloves</ref><box><224><335><313><469>,<293><517><362><599>,<511><830><574><931>,<567><910><630><1000></box>, <ref>Goggles</ref><box><331><96><409><145>,<608><415><690><462></box>, <ref>Mask<... | {"model_id": "tencent/WeVisOne-VL-4B", "prompt": "Locate all the instances that match the following description: Coverall. Face Shield. Gloves. Goggles. Mask.", "classes": ["Coverall", "Face_Shield", "Gloves", "Goggles", "Mask"], "image_size": [1200, 800], "min_pixels": 16384, "max_pixels": 2073600, "duplicate_iou": 0.... | |
1,008 | 2,000 | 1,124 | {
"id": [
34,
35,
36,
37,
38
],
"area": [
70866,
108990,
118770,
117552,
2176677
],
"bbox": [
[
826,
292,
381,
186
],
[
841,
363,
346,
315
],
[
501,
59,
321,
370
],
[
... | [
{
"bbox": [
0,
10,
1986,
1124
],
"label": "Coverall",
"sub_label": "",
"alt_labels": []
},
{
"bbox": [
824,
285,
1194,
699
],
"label": "Face_Shield",
"sub_label": "",
"alt_labels": []
},
{
"bbox": [
494,
... | <ref>Coverall</ref><box><0><9><993><1000></box>, <ref>Face Shield</ref><box><412><254><597><622></box>, <ref>Gloves</ref><box><247><56><409><392>,<567><52><730><382></box>, <ref>Goggles</ref><box><413><255><596><415></box>, <ref>Mask</ref><box><414><316><595><608></box> | {"model_id": "tencent/WeVisOne-VL-4B", "prompt": "Locate all the instances that match the following description: Coverall. Face Shield. Gloves. Goggles. Mask.", "classes": ["Coverall", "Face_Shield", "Gloves", "Goggles", "Mask"], "image_size": [2000, 1124], "min_pixels": 16384, "max_pixels": 2073600, "duplicate_iou": 0... | |
1,017 | 800 | 451 | {
"id": [
85,
86,
87,
88
],
"area": [
5232,
6160,
3835,
167678
],
"bbox": [
[
454,
84,
109,
48
],
[
468,
111,
88,
70
],
[
223,
315,
65,
59
],
[
286,
36,
406,
... | [
{
"bbox": [
283,
31,
693,
451
],
"label": "Coverall",
"sub_label": "",
"alt_labels": []
},
{
"bbox": [
460,
87,
560,
126
],
"label": "Face_Shield",
"sub_label": "",
"alt_labels": [
"Goggles"
]
},
{
"bbox": ... | <ref>Coverall</ref><box><354><69><866><1000></box>, <ref>Face Shield</ref><box><575><193><700><279></box>, <ref>Gloves</ref><box><278><699><364><828></box>, <ref>Goggles</ref><box><575><194><700><276></box>, <ref>Mask</ref><box><594><249><698><399></box> | {"model_id": "tencent/WeVisOne-VL-4B", "prompt": "Locate all the instances that match the following description: Coverall. Face Shield. Gloves. Goggles. Mask.", "classes": ["Coverall", "Face_Shield", "Gloves", "Goggles", "Mask"], "image_size": [800, 451], "min_pixels": 16384, "max_pixels": 2073600, "duplicate_iou": 0.8... |
Class-list detection with WeVisOne-VL
Boxes for Coverall, Face_Shield, Gloves, Goggles, Mask on rishitdagli/cppe-5 (split test), from
tencent/WeVisOne-VL-4B.
20 images, 20 with at least one detection,
130 detections. 14 boxes share their region with a box of another class (see alt_labels).
These are zero-shot labels: no human checked them. Treat them as a first pass for review.
Columns added
detections: list of{bbox: [x1, y1, x2, y2], label, sub_label, alt_labels}.bboxis in original-image pixels.sub_labelis always empty (WeVisOne gives class labels only); it is there so the schema matchesqwen3vl-detect.py.alt_labelslists other classes the model gave the same region (IoU >= 0.8); WeVisOne answers each class on its own, so one object can carry several class names.raw_response: the model's raw answer, for re-parsing.inference_info: JSON with the model, prompt, classes, image size and settings.
Reproduction
Produced on Hugging Face Jobs (a10g-small) with the wevisone-detect.py recipe from uv-scripts. Run it yourself:
hf jobs uv run --flavor a10g-small https://huggingface.co/datasets/uv-scripts/vlm-object-detection/raw/main/wevisone-detect.py \
rishitdagli/cppe-5 <output-dataset> --classes Coverall,Face_Shield,Gloves,Goggles,Mask --split test --max-samples 20 --shuffle --seed 42
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