1

app.py

@@ -9,6 +9,11 @@ model_name = "nvidia/segformer-b0-finetuned-ade-512-512"
 model = SegformerForSemanticSegmentation.from_pretrained(model_name)
 feature_extractor = SegformerFeatureExtractor.from_pretrained(model_name)
 
+def create_color_map(num_classes):
+    """ 임의의 색상 매핑 생성 """
+    np.random.seed(42)  # 재현성을 위한 시드 설정
+    return {i: np.random.randint(0, 256, 3) for i in range(num_classes)}
+
 def segment_image(image):
     # 이미지 처리
     inputs = feature_extractor(images=image, return_tensors="pt")
@@ -22,20 +27,25 @@ def segment_image(image):
     upsampled_predictions = upsampled_logits.argmax(dim=1)
     mask = upsampled_predictions.squeeze().numpy()
 
+    # 색상 매핑
+    color_map = create_color_map(150)  # ADE20K에는 약 150개의 클래스가 있음
+    colored_mask = np.array([color_map[class_id] for class_id in mask.flatten()]).reshape(mask.shape + (3,))
+
     # 결과 반환
-    return Image.fromarray(np.uint8(mask * 255))
+    return Image.fromarray(colored_mask.astype(np.uint8))
 
 # 예시 이미지 경로
-example_images = ["image1.jpg", "image2.jpg", "image3.jpg"]
+example_images = ["path/to/image1.jpg", "path/to/image2.jpg", "path/to/image3.jpg"]
 
 # Gradio 인터페이스 설정
-demo = gr.Interface(
+iface = gr.Interface(
     fn=segment_image,
     inputs=gr.inputs.Image(type="pil"),
     outputs="image",
-    title="머신러닝 7주차 과제_3",
+    title="Image Segmentation with SegFormer",
+    description="Upload an image to segment it using SegFormer model.",
     examples=example_images
 )
 
 # 인터페이스 실행
-demo.launch()
+iface.launch()

config.json

@@ -4,12 +4,12 @@
   ],
   "attention_probs_dropout_prob": 0.0,
   "classifier_dropout_prob": 0.1,
-  "decoder_hidden_size": 768,
+  "decoder_hidden_size": 256,
   "depths": [
-    3,
-    4,
-    18,
-    3
+    2,
+    2,
+    2,
+    2
   ],
   "downsampling_rates": [
     1,
@@ -21,54 +21,316 @@
   "hidden_act": "gelu",
   "hidden_dropout_prob": 0.0,
   "hidden_sizes": [
+    32,
     64,
-    128,
-    320,
-    512
+    160,
+    256
   ],
   "id2label": {
-    "0": "road",
-    "1": "sidewalk",
-    "2": "building",
-    "3": "wall",
-    "4": "fence",
-    "5": "pole",
-    "6": "traffic light",
-    "7": "traffic sign",
-    "8": "vegetation",
-    "9": "terrain",
-    "10": "sky",
-    "11": "person",
-    "12": "rider",
-    "13": "car",
-    "14": "truck",
-    "15": "bus",
-    "16": "train",
-    "17": "motorcycle",
-    "18": "bicycle"
+    "0": "wall",
+    "1": "building",
+    "2": "sky",
+    "3": "floor",
+    "4": "tree",
+    "5": "ceiling",
+    "6": "road",
+    "7": "bed ",
+    "8": "windowpane",
+    "9": "grass",
+    "10": "cabinet",
+    "11": "sidewalk",
+    "12": "person",
+    "13": "earth",
+    "14": "door",
+    "15": "table",
+    "16": "mountain",
+    "17": "plant",
+    "18": "curtain",
+    "19": "chair",
+    "20": "car",
+    "21": "water",
+    "22": "painting",
+    "23": "sofa",
+    "24": "shelf",
+    "25": "house",
+    "26": "sea",
+    "27": "mirror",
+    "28": "rug",
+    "29": "field",
+    "30": "armchair",
+    "31": "seat",
+    "32": "fence",
+    "33": "desk",
+    "34": "rock",
+    "35": "wardrobe",
+    "36": "lamp",
+    "37": "bathtub",
+    "38": "railing",
+    "39": "cushion",
+    "40": "base",
+    "41": "box",
+    "42": "column",
+    "43": "signboard",
+    "44": "chest of drawers",
+    "45": "counter",
+    "46": "sand",
+    "47": "sink",
+    "48": "skyscraper",
+    "49": "fireplace",
+    "50": "refrigerator",
+    "51": "grandstand",
+    "52": "path",
+    "53": "stairs",
+    "54": "runway",
+    "55": "case",
+    "56": "pool table",
+    "57": "pillow",
+    "58": "screen door",
+    "59": "stairway",
+    "60": "river",
+    "61": "bridge",
+    "62": "bookcase",
+    "63": "blind",
+    "64": "coffee table",
+    "65": "toilet",
+    "66": "flower",
+    "67": "book",
+    "68": "hill",
+    "69": "bench",
+    "70": "countertop",
+    "71": "stove",
+    "72": "palm",
+    "73": "kitchen island",
+    "74": "computer",
+    "75": "swivel chair",
+    "76": "boat",
+    "77": "bar",
+    "78": "arcade machine",
+    "79": "hovel",
+    "80": "bus",
+    "81": "towel",
+    "82": "light",
+    "83": "truck",
+    "84": "tower",
+    "85": "chandelier",
+    "86": "awning",
+    "87": "streetlight",
+    "88": "booth",
+    "89": "television receiver",
+    "90": "airplane",
+    "91": "dirt track",
+    "92": "apparel",
+    "93": "pole",
+    "94": "land",
+    "95": "bannister",
+    "96": "escalator",
+    "97": "ottoman",
+    "98": "bottle",
+    "99": "buffet",
+    "100": "poster",
+    "101": "stage",
+    "102": "van",
+    "103": "ship",
+    "104": "fountain",
+    "105": "conveyer belt",
+    "106": "canopy",
+    "107": "washer",
+    "108": "plaything",
+    "109": "swimming pool",
+    "110": "stool",
+    "111": "barrel",
+    "112": "basket",
+    "113": "waterfall",
+    "114": "tent",
+    "115": "bag",
+    "116": "minibike",
+    "117": "cradle",
+    "118": "oven",
+    "119": "ball",
+    "120": "food",
+    "121": "step",
+    "122": "tank",
+    "123": "trade name",
+    "124": "microwave",
+    "125": "pot",
+    "126": "animal",
+    "127": "bicycle",
+    "128": "lake",
+    "129": "dishwasher",
+    "130": "screen",
+    "131": "blanket",
+    "132": "sculpture",
+    "133": "hood",
+    "134": "sconce",
+    "135": "vase",
+    "136": "traffic light",
+    "137": "tray",
+    "138": "ashcan",
+    "139": "fan",
+    "140": "pier",
+    "141": "crt screen",
+    "142": "plate",
+    "143": "monitor",
+    "144": "bulletin board",
+    "145": "shower",
+    "146": "radiator",
+    "147": "glass",
+    "148": "clock",
+    "149": "flag"
   },
   "image_size": 224,
   "initializer_range": 0.02,
   "label2id": {
-    "bicycle": 18,
-    "building": 2,
-    "bus": 15,
-    "car": 13,
-    "fence": 4,
-    "motorcycle": 17,
-    "person": 11,
-    "pole": 5,
-    "rider": 12,
-    "road": 0,
-    "sidewalk": 1,
-    "sky": 10,
-    "terrain": 9,
-    "traffic light": 6,
-    "traffic sign": 7,
-    "train": 16,
-    "truck": 14,
-    "vegetation": 8,
-    "wall": 3
+    "airplane": 90,
+    "animal": 126,
+    "apparel": 92,
+    "arcade machine": 78,
+    "armchair": 30,
+    "ashcan": 138,
+    "awning": 86,
+    "bag": 115,
+    "ball": 119,
+    "bannister": 95,
+    "bar": 77,
+    "barrel": 111,
+    "base": 40,
+    "basket": 112,
+    "bathtub": 37,
+    "bed ": 7,
+    "bench": 69,
+    "bicycle": 127,
+    "blanket": 131,
+    "blind": 63,
+    "boat": 76,
+    "book": 67,
+    "bookcase": 62,
+    "booth": 88,
+    "bottle": 98,
+    "box": 41,
+    "bridge": 61,
+    "buffet": 99,
+    "building": 1,
+    "bulletin board": 144,
+    "bus": 80,
+    "cabinet": 10,
+    "canopy": 106,
+    "car": 20,
+    "case": 55,
+    "ceiling": 5,
+    "chair": 19,
+    "chandelier": 85,
+    "chest of drawers": 44,
+    "clock": 148,
+    "coffee table": 64,
+    "column": 42,
+    "computer": 74,
+    "conveyer belt": 105,
+    "counter": 45,
+    "countertop": 70,
+    "cradle": 117,
+    "crt screen": 141,
+    "curtain": 18,
+    "cushion": 39,
+    "desk": 33,
+    "dirt track": 91,
+    "dishwasher": 129,
+    "door": 14,
+    "earth": 13,
+    "escalator": 96,
+    "fan": 139,
+    "fence": 32,
+    "field": 29,
+    "fireplace": 49,
+    "flag": 149,
+    "floor": 3,
+    "flower": 66,
+    "food": 120,
+    "fountain": 104,
+    "glass": 147,
+    "grandstand": 51,
+    "grass": 9,
+    "hill": 68,
+    "hood": 133,
+    "house": 25,
+    "hovel": 79,
+    "kitchen island": 73,
+    "lake": 128,
+    "lamp": 36,
+    "land": 94,
+    "light": 82,
+    "microwave": 124,
+    "minibike": 116,
+    "mirror": 27,
+    "monitor": 143,
+    "mountain": 16,
+    "ottoman": 97,
+    "oven": 118,
+    "painting": 22,
+    "palm": 72,
+    "path": 52,
+    "person": 12,
+    "pier": 140,
+    "pillow": 57,
+    "plant": 17,
+    "plate": 142,
+    "plaything": 108,
+    "pole": 93,
+    "pool table": 56,
+    "poster": 100,
+    "pot": 125,
+    "radiator": 146,
+    "railing": 38,
+    "refrigerator": 50,
+    "river": 60,
+    "road": 6,
+    "rock": 34,
+    "rug": 28,
+    "runway": 54,
+    "sand": 46,
+    "sconce": 134,
+    "screen": 130,
+    "screen door": 58,
+    "sculpture": 132,
+    "sea": 26,
+    "seat": 31,
+    "shelf": 24,
+    "ship": 103,
+    "shower": 145,
+    "sidewalk": 11,
+    "signboard": 43,
+    "sink": 47,
+    "sky": 2,
+    "skyscraper": 48,
+    "sofa": 23,
+    "stage": 101,
+    "stairs": 53,
+    "stairway": 59,
+    "step": 121,
+    "stool": 110,
+    "stove": 71,
+    "streetlight": 87,
+    "swimming pool": 109,
+    "swivel chair": 75,
+    "table": 15,
+    "tank": 122,
+    "television receiver": 89,
+    "tent": 114,
+    "toilet": 65,
+    "towel": 81,
+    "tower": 84,
+    "trade name": 123,
+    "traffic light": 136,
+    "tray": 137,
+    "tree": 4,
+    "truck": 83,
+    "van": 102,
+    "vase": 135,
+    "wall": 0,
+    "wardrobe": 35,
+    "washer": 107,
+    "water": 21,
+    "waterfall": 113,
+    "windowpane": 8
   },
   "layer_norm_eps": 1e-06,
   "mlp_ratios": [

preprocessor_config.json

@@ -12,7 +12,7 @@
     0.224,
     0.225
   ],
-  "reduce_labels": false,
+  "reduce_labels": true,
   "resample": 2,
   "size": 512
 }

pytorch_model.bin

@@ -1,3 +1,3 @@
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-oid sha256:4b3916b8781255eaa6b596be75eb4610001e2ff18083a4aa897539e1d1f41f3f
-size 189204985
+oid sha256:0f4df97633cbedd558ecffa3ad228ace5af37e082678390b45a9d22745787c61
+size 15092257

tf_model.h5

@@ -1,3 +1,3 @@
 version https://git-lfs.github.com/spec/v1
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-size 189787044
+oid sha256:d38f99e2a8e73bbdb4635669be5bfcbbfc85b4b5c1ac75d36b47312c7fc5d06e
+size 15285696