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Add config from convert_rt_detr_original_pytorch_checkpoint_to_pytorch.py

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  1. README.md +199 -0
  2. config.json +273 -0
README.md ADDED
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+ ---
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+ library_name: transformers
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+ tags: []
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+ ---
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+ # Model Card for Model ID
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+ <!-- Provide a quick summary of what the model is/does. -->
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+ ## Model Details
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+ This is the model card of a 🤗 transformers model that has been pushed on the Hub. This model card has been automatically generated.
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+ ## How to Get Started with the Model
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config.json ADDED
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+ {
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+ "activation_dropout": 0.0,
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+ "activation_function": "silu",
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+ "anchor_image_size": [
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+ 640,
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+ 640
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+ ],
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+ "architectures": [
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+ "RTDetrForObjectDetection"
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+ ],
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+ "attention_dropout": 0.0,
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+ "auxiliary_loss": true,
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+ "batch_norm_eps": 1e-05,
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+ "box_noise_scale": 1.0,
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+ "d_model": 256,
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+ "decoder_activation_function": "relu",
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+ "decoder_attention_heads": 8,
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+ "decoder_ffn_dim": 1024,
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+ "decoder_in_channels": [
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+ 384,
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+ 384,
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+ 384
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+ ],
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+ "decoder_layers": 6,
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+ "decoder_n_points": 4,
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+ "depths": [
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+ 3,
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+ 4,
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+ 23,
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+ 3
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+ ],
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+ "disable_custom_kernels": true,
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+ "downsample_in_bottleneck": false,
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+ "downsample_in_first_stage": false,
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+ "dropout": 0.0,
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+ "embedding_size": 64,
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+ "encode_proj_layers": [
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+ 2
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+ ],
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+ "encoder_activation_function": "gelu",
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+ "encoder_attention_heads": 8,
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+ "encoder_ffn_dim": 2048,
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+ "encoder_hidden_dim": 384,
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+ "encoder_in_channels": [
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+ 512,
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+ 1024,
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+ 2048
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+ ],
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+ "encoder_layers": 1,
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+ "eos_coefficient": 0.0001,
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+ "eval_size": null,
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+ "feat_strides": [
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+ 8,
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+ 16,
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+ 32
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+ ],
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+ "focal_loss_alpha": 0.75,
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+ "focal_loss_gamma": 2.0,
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+ "hidden_act": "relu",
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+ "hidden_expansion": 1.0,
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+ "hidden_sizes": [
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+ 256,
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+ 512,
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+ 1024,
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+ 2048
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+ ],
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+ "id2label": {
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+ "0": "person",
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+ "1": "bicycle",
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+ "2": "car",
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+ "3": "motorbike",
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+ "4": "aeroplane",
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+ "5": "bus",
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+ "6": "train",
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+ "7": "truck",
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+ "8": "boat",
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+ "9": "traffic light",
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+ "10": "fire hydrant",
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+ "11": "stop sign",
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+ "12": "parking meter",
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+ "13": "bench",
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+ "14": "bird",
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+ "15": "cat",
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+ "16": "dog",
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+ "17": "horse",
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+ "18": "sheep",
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+ "19": "cow",
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+ "20": "elephant",
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+ "21": "bear",
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+ "22": "zebra",
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+ "23": "giraffe",
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+ "24": "backpack",
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+ "25": "umbrella",
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+ "26": "handbag",
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+ "27": "tie",
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+ "28": "suitcase",
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+ "29": "frisbee",
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+ "30": "skis",
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+ "31": "snowboard",
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+ "32": "sports ball",
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+ "33": "kite",
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+ "34": "baseball bat",
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+ "35": "baseball glove",
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+ "36": "skateboard",
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+ "37": "surfboard",
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+ "38": "tennis racket",
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+ "39": "bottle",
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+ "40": "wine glass",
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+ "41": "cup",
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+ "42": "fork",
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+ "43": "knife",
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+ "44": "spoon",
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+ "45": "bowl",
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+ "46": "banana",
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+ "47": "apple",
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+ "48": "sandwich",
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+ "49": "orange",
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+ "50": "broccoli",
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+ "51": "carrot",
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+ "52": "hot dog",
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+ "53": "pizza",
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+ "54": "donut",
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+ "55": "cake",
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+ "56": "chair",
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+ "57": "sofa",
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+ "58": "pottedplant",
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+ "59": "bed",
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+ "60": "diningtable",
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+ "61": "toilet",
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+ "62": "tvmonitor",
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+ "63": "laptop",
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+ "64": "mouse",
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+ "65": "remote",
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+ "66": "keyboard",
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+ "67": "cell phone",
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+ "68": "microwave",
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+ "69": "oven",
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+ "70": "toaster",
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+ "71": "sink",
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+ "72": "refrigerator",
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+ "73": "book",
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+ "74": "clock",
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+ "75": "vase",
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+ "76": "scissors",
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+ "77": "teddy bear",
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+ "78": "hair drier",
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+ "79": "toothbrush"
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+ },
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+ "initializer_range": 0.01,
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+ "is_encoder_decoder": true,
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+ "label2id": {
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+ "aeroplane": 4,
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+ "apple": 47,
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+ "backpack": 24,
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+ "banana": 46,
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+ "baseball bat": 34,
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+ "baseball glove": 35,
158
+ "bear": 21,
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+ "bed": 59,
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+ "bench": 13,
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+ "bicycle": 1,
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+ "bird": 14,
163
+ "boat": 8,
164
+ "book": 73,
165
+ "bottle": 39,
166
+ "bowl": 45,
167
+ "broccoli": 50,
168
+ "bus": 5,
169
+ "cake": 55,
170
+ "car": 2,
171
+ "carrot": 51,
172
+ "cat": 15,
173
+ "cell phone": 67,
174
+ "chair": 56,
175
+ "clock": 74,
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+ "cow": 19,
177
+ "cup": 41,
178
+ "diningtable": 60,
179
+ "dog": 16,
180
+ "donut": 54,
181
+ "elephant": 20,
182
+ "fire hydrant": 10,
183
+ "fork": 42,
184
+ "frisbee": 29,
185
+ "giraffe": 23,
186
+ "hair drier": 78,
187
+ "handbag": 26,
188
+ "horse": 17,
189
+ "hot dog": 52,
190
+ "keyboard": 66,
191
+ "kite": 33,
192
+ "knife": 43,
193
+ "laptop": 63,
194
+ "microwave": 68,
195
+ "motorbike": 3,
196
+ "mouse": 64,
197
+ "orange": 49,
198
+ "oven": 69,
199
+ "parking meter": 12,
200
+ "person": 0,
201
+ "pizza": 53,
202
+ "pottedplant": 58,
203
+ "refrigerator": 72,
204
+ "remote": 65,
205
+ "sandwich": 48,
206
+ "scissors": 76,
207
+ "sheep": 18,
208
+ "sink": 71,
209
+ "skateboard": 36,
210
+ "skis": 30,
211
+ "snowboard": 31,
212
+ "sofa": 57,
213
+ "spoon": 44,
214
+ "sports ball": 32,
215
+ "stop sign": 11,
216
+ "suitcase": 28,
217
+ "surfboard": 37,
218
+ "teddy bear": 77,
219
+ "tennis racket": 38,
220
+ "tie": 27,
221
+ "toaster": 70,
222
+ "toilet": 61,
223
+ "toothbrush": 79,
224
+ "traffic light": 9,
225
+ "train": 6,
226
+ "truck": 7,
227
+ "tvmonitor": 62,
228
+ "umbrella": 25,
229
+ "vase": 75,
230
+ "wine glass": 40,
231
+ "zebra": 22
232
+ },
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+ "label_noise_ratio": 0.5,
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+ "layer_norm_eps": 1e-05,
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+ "layer_type": "bottleneck",
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+ "learn_initial_query": false,
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+ "matcher_alpha": 0.25,
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+ "matcher_bbox_cost": 5.0,
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+ "matcher_class_cost": 2.0,
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+ "matcher_gamma": 2.0,
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+ "matcher_giou_cost": 2.0,
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+ "model_type": "rt_detr",
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+ "normalize_before": false,
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+ "num_channels": 3,
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+ "num_denoising": 100,
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+ "num_feature_levels": 3,
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+ "num_queries": 300,
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+ "out_features": [
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+ "stage2",
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+ "stage3",
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+ "stage4"
252
+ ],
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+ "out_indices": [
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+ 2,
255
+ 3,
256
+ 4
257
+ ],
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+ "positional_encoding_temperature": 10000,
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+ "stage_names": [
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+ "stem",
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+ "stage1",
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+ "stage2",
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+ "stage3",
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+ "stage4"
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+ ],
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+ "torch_dtype": "float32",
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+ "transformers_version": "4.42.0.dev0",
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+ "use_focal_loss": true,
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+ "weight_loss_bbox": 5.0,
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+ "weight_loss_giou": 2.0,
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+ "weight_loss_vfl": 1.0,
272
+ "with_box_refine": true
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+ }