nsa436 commited on
Commit
5323010
1 Parent(s): e2bcb48

remove files

Browse files
config.json CHANGED
@@ -1,8 +1,9 @@
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  {
 
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  "activation_dropout": 0.0,
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  "activation_function": "relu",
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  "architectures": [
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- "DetrForSegmentation"
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  ],
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  "attention_dropout": 0.0,
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  "auxiliary_loss": false,
@@ -10,7 +11,6 @@
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  "bbox_cost": 5,
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  "bbox_loss_coefficient": 5,
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- "classifier_dropout": 0.0,
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  "d_model": 256,
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  "decoder_attention_heads": 8,
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  "decoder_ffn_dim": 2048,
@@ -27,512 +27,14 @@
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  "giou_cost": 2,
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  "giou_loss_coefficient": 2,
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  "id2label": {
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- "0": "N/A",
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- "1": "person",
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- "10": "traffic light",
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- "100": "cardboard",
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- "101": "carpet",
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- "102": "ceiling-other",
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- "103": "ceiling-tile",
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- "104": "cloth",
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- "105": "clothes",
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- "106": "clouds",
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- "107": "counter",
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- "108": "cupboard",
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- "109": "curtain",
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- "11": "fire hydrant",
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- "110": "desk-stuff",
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- "111": "dirt",
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- "112": "door-stuff",
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- "113": "fence",
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- "114": "floor-marble",
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- "115": "floor-other",
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- "116": "floor-stone",
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- "117": "floor-tile",
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- "118": "floor-wood",
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- "119": "flower",
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- "12": "street sign",
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- "120": "fog",
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- "121": "food-other",
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- "122": "fruit",
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- "123": "furniture-other",
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- "124": "grass",
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- "125": "gravel",
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- "126": "ground-other",
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- "127": "hill",
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- "128": "house",
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- "129": "leaves",
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- "13": "stop sign",
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- "130": "light",
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- "131": "mat",
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- "132": "metal",
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- "133": "mirror-stuff",
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- "134": "moss",
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- "135": "mountain",
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- "136": "mud",
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- "137": "napkin",
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- "138": "net",
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- "139": "paper",
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- "14": "parking meter",
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- "140": "pavement",
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- "141": "pillow",
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- "142": "plant-other",
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- "143": "plastic",
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- "144": "platform",
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- "145": "playingfield",
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- "146": "railing",
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- "147": "railroad",
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- "148": "river",
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- "149": "road",
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- "15": "bench",
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- "150": "rock",
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- "151": "roof",
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- "152": "rug",
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- "153": "salad",
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- "154": "sand",
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- "155": "sea",
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- "156": "shelf",
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- "157": "sky-other",
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- "158": "skyscraper",
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- "159": "snow",
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- "16": "bird",
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- "160": "solid-other",
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- "161": "stairs",
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- "162": "stone",
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- "163": "straw",
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- "164": "structural-other",
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- "165": "table",
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- "166": "tent",
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- "167": "textile-other",
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- "168": "towel",
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- "169": "tree",
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- "17": "cat",
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- "170": "vegetable",
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- "171": "wall-brick",
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- "172": "wall-concrete",
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- "173": "wall-other",
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- "174": "wall-panel",
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- "175": "wall-stone",
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- "176": "wall-tile",
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- "177": "wall-wood",
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- "178": "water-other",
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- "179": "waterdrops",
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- "18": "dog",
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- "180": "window-blind",
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- "181": "window-other",
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- "182": "wood",
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- "183": "LABEL_183",
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- "184": "LABEL_184",
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- "185": "LABEL_185",
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- "186": "LABEL_186",
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- "187": "LABEL_187",
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- "188": "LABEL_188",
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- "189": "LABEL_189",
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- "19": "horse",
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- "190": "LABEL_190",
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- "191": "LABEL_191",
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- "192": "LABEL_192",
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- "193": "LABEL_193",
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- "194": "LABEL_194",
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- "195": "LABEL_195",
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- "196": "LABEL_196",
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- "197": "LABEL_197",
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- "198": "LABEL_198",
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- "199": "LABEL_199",
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- "2": "bicycle",
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- "20": "sheep",
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- "200": "LABEL_200",
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- "201": "LABEL_201",
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- "202": "LABEL_202",
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- "203": "LABEL_203",
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- "204": "LABEL_204",
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- "205": "LABEL_205",
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- "206": "LABEL_206",
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- "207": "LABEL_207",
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- "208": "LABEL_208",
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- "209": "LABEL_209",
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- "21": "cow",
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- "210": "LABEL_210",
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- "211": "LABEL_211",
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- "212": "LABEL_212",
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- "213": "LABEL_213",
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- "214": "LABEL_214",
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- "215": "LABEL_215",
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- "216": "LABEL_216",
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- "217": "LABEL_217",
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- "218": "LABEL_218",
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- "219": "LABEL_219",
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- "22": "elephant",
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- "220": "LABEL_220",
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- "221": "LABEL_221",
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- "222": "LABEL_222",
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- "223": "LABEL_223",
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- "224": "LABEL_224",
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- "225": "LABEL_225",
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- "226": "LABEL_226",
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- "227": "LABEL_227",
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- "228": "LABEL_228",
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- "229": "LABEL_229",
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- "23": "bear",
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- "230": "LABEL_230",
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- "231": "LABEL_231",
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- "232": "LABEL_232",
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- "233": "LABEL_233",
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- "234": "LABEL_234",
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- "235": "LABEL_235",
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- "236": "LABEL_236",
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- "237": "LABEL_237",
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- "238": "LABEL_238",
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- "239": "LABEL_239",
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- "24": "zebra",
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- "240": "LABEL_240",
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- "241": "LABEL_241",
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- "242": "LABEL_242",
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- "243": "LABEL_243",
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- "244": "LABEL_244",
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- "245": "LABEL_245",
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- "246": "LABEL_246",
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- "247": "LABEL_247",
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- "248": "LABEL_248",
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- "249": "LABEL_249",
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- "25": "giraffe",
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- "26": "hat",
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- "27": "backpack",
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- "28": "umbrella",
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- "29": "shoe",
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- "3": "car",
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- "30": "eye glasses",
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- "31": "handbag",
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- "32": "tie",
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- "33": "suitcase",
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- "34": "frisbee",
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- "35": "skis",
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- "36": "snowboard",
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- "37": "sports ball",
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- "38": "kite",
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- "39": "baseball bat",
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- "4": "motorcycle",
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- "40": "baseball glove",
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- "41": "skateboard",
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- "42": "surfboard",
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- "43": "tennis racket",
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- "44": "bottle",
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- "45": "plate",
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- "46": "wine glass",
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- "47": "cup",
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- "48": "fork",
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- "49": "knife",
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- "5": "airplane",
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- "50": "spoon",
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- "51": "bowl",
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- "52": "banana",
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- "53": "apple",
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- "54": "sandwich",
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- "55": "orange",
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- "56": "broccoli",
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- "57": "carrot",
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- "58": "hot dog",
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- "59": "pizza",
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- "6": "bus",
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- "60": "donut",
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- "61": "cake",
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- "62": "chair",
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- "63": "couch",
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- "64": "potted plant",
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- "65": "bed",
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- "66": "mirror",
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- "67": "dining table",
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- "68": "window",
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- "69": "desk",
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- "7": "train",
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- "70": "toilet",
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- "71": "door",
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- "72": "tv",
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- "73": "laptop",
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- "74": "mouse",
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- "75": "remote",
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- "76": "keyboard",
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- "77": "cell phone",
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- "78": "microwave",
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- "79": "oven",
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- "8": "truck",
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- "80": "toaster",
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- "81": "sink",
261
- "82": "refrigerator",
262
- "83": "blender",
263
- "84": "book",
264
- "85": "clock",
265
- "86": "vase",
266
- "87": "scissors",
267
- "88": "teddy bear",
268
- "89": "hair drier",
269
- "9": "boat",
270
- "90": "toothbrush",
271
- "91": "hair brush",
272
- "92": "banner",
273
- "93": "blanket",
274
- "94": "branch",
275
- "95": "bridge",
276
- "96": "building-other",
277
- "97": "bush",
278
- "98": "cabinet",
279
- "99": "cage"
280
- },
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  "init_std": 0.02,
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  "init_xavier_std": 1.0,
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  "is_encoder_decoder": true,
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  "label2id": {
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- "dog": 18,
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- "flower": 119,
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- "gravel": 125,
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- "moss": 134,
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- "mountain": 135,
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- "napkin": 137,
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- "platform": 144,
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- "playingfield": 145,
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- "potted plant": 64,
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- "snow": 159,
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- "snowboard": 36,
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- "solid-other": 160,
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- "spoon": 50,
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- "sports ball": 37,
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- "stone": 162,
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- "wall-stone": 175,
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- "wall-tile": 176,
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- "wall-wood": 177,
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- "water-other": 178,
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- "waterdrops": 179,
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- "window": 68,
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- "window-blind": 180,
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- "window-other": 181,
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- "wine glass": 46,
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- "wood": 182,
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- "zebra": 24
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- },
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  "mask_loss_coefficient": 1,
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  "max_position_embeddings": 1024,
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  "model_type": "detr",
@@ -540,5 +42,6 @@
540
  "num_queries": 100,
541
  "position_embedding_type": "sine",
542
  "scale_embedding": false,
543
- "transformers_version": "4.7.0.dev0"
544
- }
 
 
1
  {
2
+ "_name_or_path": "facebook/detr-resnet-50",
3
  "activation_dropout": 0.0,
4
  "activation_function": "relu",
5
  "architectures": [
6
+ "DetrForObjectDetection"
7
  ],
8
  "attention_dropout": 0.0,
9
  "auxiliary_loss": false,
 
11
  "bbox_cost": 5,
12
  "bbox_loss_coefficient": 5,
13
  "class_cost": 1,
 
14
  "d_model": 256,
15
  "decoder_attention_heads": 8,
16
  "decoder_ffn_dim": 2048,
 
27
  "giou_cost": 2,
28
  "giou_loss_coefficient": 2,
29
  "id2label": {
30
+ "0": "face",
31
+ },
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
32
  "init_std": 0.02,
33
  "init_xavier_std": 1.0,
34
  "is_encoder_decoder": true,
35
  "label2id": {
36
+ "face": 1,
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+ },
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
38
  "mask_loss_coefficient": 1,
39
  "max_position_embeddings": 1024,
40
  "model_type": "detr",
 
42
  "num_queries": 100,
43
  "position_embedding_type": "sine",
44
  "scale_embedding": false,
45
+ "torch_dtype": "float32",
46
+ "transformers_version": "4.17.0"
47
+ }
detr_256_6_6_torchvision.yaml DELETED
@@ -1,45 +0,0 @@
1
- MODEL:
2
- META_ARCHITECTURE: "Detr"
3
- WEIGHTS: "detectron2://ImageNetPretrained/torchvision/R-50.pkl"
4
- PIXEL_MEAN: [123.675, 116.280, 103.530]
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- PIXEL_STD: [58.395, 57.120, 57.375]
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- MASK_ON: False
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- RESNETS:
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- DEPTH: 50
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- STRIDE_IN_1X1: False
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- OUT_FEATURES: ["res2", "res3", "res4", "res5"]
11
- DETR:
12
- GIOU_WEIGHT: 2.0
13
- L1_WEIGHT: 5.0
14
- NUM_OBJECT_QUERIES: 100
15
- DATASETS:
16
- TRAIN: ("coco_2017_train",)
17
- TEST: ("coco_2017_val",)
18
- SOLVER:
19
- IMS_PER_BATCH: 64
20
- BASE_LR: 0.0001
21
- STEPS: (369600,)
22
- MAX_ITER: 554400
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- WARMUP_FACTOR: 1.0
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- WARMUP_ITERS: 10
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- WEIGHT_DECAY: 0.0001
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- OPTIMIZER: "ADAMW"
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- BACKBONE_MULTIPLIER: 0.1
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- CLIP_GRADIENTS:
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- ENABLED: True
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- CLIP_TYPE: "full_model"
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- CLIP_VALUE: 0.01
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- NORM_TYPE: 2.0
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- INPUT:
34
- MIN_SIZE_TRAIN: (480, 512, 544, 576, 608, 640, 672, 704, 736, 768, 800)
35
- CROP:
36
- ENABLED: True
37
- TYPE: "absolute_range"
38
- SIZE: (384, 600)
39
- FORMAT: "RGB"
40
- TEST:
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- EVAL_PERIOD: 4000
42
- DATALOADER:
43
- FILTER_EMPTY_ANNOTATIONS: False
44
- NUM_WORKERS: 4
45
- VERSION: 2
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
detr_segm_256_6_6_torchvision.yaml DELETED
@@ -1,46 +0,0 @@
1
- MODEL:
2
- META_ARCHITECTURE: "Detr"
3
- # WEIGHTS: "detectron2://ImageNetPretrained/torchvision/R-50.pkl"
4
- PIXEL_MEAN: [123.675, 116.280, 103.530]
5
- PIXEL_STD: [58.395, 57.120, 57.375]
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- MASK_ON: True
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- RESNETS:
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- DEPTH: 50
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- OUT_FEATURES: ["res2", "res3", "res4", "res5"]
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- DETR:
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- GIOU_WEIGHT: 2.0
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- L1_WEIGHT: 5.0
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- NUM_OBJECT_QUERIES: 100
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- FROZEN_WEIGHTS: ''
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- DATASETS:
17
- TRAIN: ("coco_2017_train",)
18
- TEST: ("coco_2017_val",)
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- SOLVER:
20
- IMS_PER_BATCH: 64
21
- BASE_LR: 0.0001
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- STEPS: (55440,)
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- WARMUP_FACTOR: 1.0
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- CLIP_TYPE: "full_model"
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- CLIP_VALUE: 0.01
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- NORM_TYPE: 2.0
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- MIN_SIZE_TRAIN: (480, 512, 544, 576, 608, 640, 672, 704, 736, 768, 800)
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- CROP:
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- ENABLED: True
38
- TYPE: "absolute_range"
39
- SIZE: (384, 600)
40
- FORMAT: "RGB"
41
- TEST:
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- EVAL_PERIOD: 4000
43
- DATALOADER:
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- FILTER_EMPTY_ANNOTATIONS: False
45
- NUM_WORKERS: 4
46
- VERSION: 2
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
preprocessor_config.json CHANGED
@@ -2,7 +2,7 @@
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  "do_normalize": true,
3
  "do_resize": true,
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  "feature_extractor_type": "DetrFeatureExtractor",
5
- "format": "coco_panoptic",
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  "image_mean": [
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@@ -15,4 +15,4 @@
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17
  "size": 800
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- }
 
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  "do_normalize": true,
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  "do_resize": true,
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  "feature_extractor_type": "DetrFeatureExtractor",
5
+ "format": "coco_detection",
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  "image_mean": [
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  0.485,
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  0.456,
 
15
  ],
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  "max_size": 1333,
17
  "size": 800
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