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@ -14,3 +14,4 @@
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*.pb filter=lfs diff=lfs merge=lfs -text
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*.pb filter=lfs diff=lfs merge=lfs -text
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*.pt filter=lfs diff=lfs merge=lfs -text
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*.pt filter=lfs diff=lfs merge=lfs -text
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*.pth filter=lfs diff=lfs merge=lfs -text
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*.pth filter=lfs diff=lfs merge=lfs -text
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model.safetensors filter=lfs diff=lfs merge=lfs -text
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@ -45,8 +45,9 @@ import requests
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url = "http://images.cocodataset.org/val2017/000000039769.jpg"
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url = "http://images.cocodataset.org/val2017/000000039769.jpg"
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image = Image.open(requests.get(url, stream=True).raw)
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image = Image.open(requests.get(url, stream=True).raw)
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processor = DetrImageProcessor.from_pretrained("facebook/detr-resnet-101")
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# you can specify the revision tag if you don't want the timm dependency
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model = DetrForObjectDetection.from_pretrained("facebook/detr-resnet-101")
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processor = DetrImageProcessor.from_pretrained("facebook/detr-resnet-101", revision="no_timm")
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model = DetrForObjectDetection.from_pretrained("facebook/detr-resnet-101", revision="no_timm")
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inputs = processor(images=image, return_tensors="pt")
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inputs = processor(images=image, return_tensors="pt")
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outputs = model(**inputs)
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outputs = model(**inputs)
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2100
config.json
2100
config.json
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@ -1,7 +1,5 @@
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{
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{
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"do_normalize": true,
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"do_normalize": true,
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"do_pad": true,
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"do_rescale": true,
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"do_resize": true,
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"do_resize": true,
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"format": "coco_detection",
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"format": "coco_detection",
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"image_mean": [
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"image_mean": [
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@ -9,14 +7,11 @@
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0.456,
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0.456,
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0.406
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0.406
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],
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],
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"image_processor_type": "DetrImageProcessor",
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"image_std": [
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"image_std": [
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0.229,
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0.229,
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0.224,
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0.224,
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0.225
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0.225
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],
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],
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"resample": 2,
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"rescale_factor": 0.00392156862745098,
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"size": {
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"size": {
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"longest_edge": 1333,
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"longest_edge": 1333,
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"shortest_edge": 800
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"shortest_edge": 800
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BIN
pytorch_model.bin (Stored with Git LFS)
BIN
pytorch_model.bin (Stored with Git LFS)
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