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check.py

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+import os
+
+label_path = "label"
+label_files = set([os.path.splitext(file)[0] for file in os.listdir(label_path) if file.endswith(".png")])
+
+data_path = "data"
+data_files = set([os.path.splitext(file)[0] for file in os.listdir(data_path) if file.endswith(".png")])
+txt_files = set([os.path.splitext(file)[0] for file in os.listdir(data_path) if file.endswith(".txt")])
+
+
+if label_files==data_files:
+    print("data_files")
+if label_files==txt_files:
+    print("txt_files")

data.zip

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+version https://git-lfs.github.com/spec/v1
+oid sha256:bf5218c09fa967674956541bec37f30052424e2b8a6dc674d22154f99b45fe17
+size 4116366493

figure_generate.py

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+from PIL import Image, ImageDraw, ImageFilter
+import numpy as np
+import random
+
+class SimplePolygon:
+    pow2 = None
+
+    def __init__(self, file_name, depth_name, tags_name,resolution=(512, 512), init_color=(255, 255, 255)):
+        self.file_name = file_name
+        self.depth_name = depth_name
+        self.tags_name = tags_name
+        self.width = resolution[0]
+        self.height = resolution[1]
+        self.components= [set([(wi, hi) for wi in range(512) for hi in range(512)])]
+        self.img1 = np.full((self.width, self.height, 3), np.random.randint(0, 256, size=(3,), dtype=np.uint8), dtype=np.uint8)
+        self.img2 = np.zeros([self.width, self.height, 3], dtype=np.uint8)
+        self.count = 0
+        if self.pow2 is None:
+            self.pow2 = [x**2 for x in range(max(resolution[0],resolution[1])+1)]
+
+    def generate(self):
+        layer = np.zeros_like(self.components, dtype=np.uint16)
+        noise = np.zeros(3, dtype=np.int16)
+        if random.randint(1, 5)==1:
+            noise = np.random.randint(-10, 10, size=(3,), dtype=np.int16)
+        for i in range(len(self.components)):
+            for j in range(i-1, -1, -1):
+                if not self.components[i].isdisjoint(self.components[j]):
+                    layer[i]=layer[j]+1
+                    color = np.random.randint(0, 255, size=(3,), dtype=np.int16)
+                    vec = np.random.randint(0, 255, size=(3,), dtype=np.int16)
+                    ep = np.random.normal(0, 2, size=(2,))
+                    for wi, hi in self.components[i]:
+                        self.img1[wi][hi] = np.abs((color + vec * (ep[0] * wi / self.width + ep[1] * hi / self.height)+noise) % 512 - 256).astype(np.uint8)
+                    break
+        self.layer_max = np.max(layer)
+        normalized_layer = ( (255 * layer) // self.layer_max).astype(np.uint8)
+        for wi in range(self.width):
+            for hi in range(self.height):
+                for i in range(len(self.components)-1, -1, -1):
+                    if (wi,hi) in self.components[i]:
+                        self.img2[wi][hi][0] = normalized_layer[i]          
+                        self.img2[wi][hi][1] = normalized_layer[i]          
+                        self.img2[wi][hi][2] = normalized_layer[i]          
+                        break
+
+    def add_rect(self):
+        left_top = [random.randint(0, self.width//10*9), random.randint(0, self.height//10*9)]
+        poly_width = random.randint(60, self.width//2)
+        poly_height = random.randint(60, self.height//2)
+        poly = set()
+        for wi in range(left_top[0], min(left_top[0]+poly_width, self.width)):
+            for hi in range(left_top[1], min(left_top[1]+poly_height, self.height)):
+                poly.add((wi, hi))
+        self.components.append(poly)
+        return poly
+
+    def add_ellipse(self):
+        center = [random.randint(self.width//10, self.width//10*9), random.randint(self.height//10, self.height//10*9)]
+        radius_width = random.randint(60, self.width//4)
+        radius_height = random.randint(60, self.height//4)
+        poly = set()
+        r = radius_width**2 * radius_height**2
+        h2 = radius_height**2
+        w2 = radius_width**2
+        for wi in range(self.width):
+            xx = h2 * self.pow2[abs(wi-center[0])]
+            if xx > r:
+                continue
+            for hi in range(self.height):
+                if xx + w2 * self.pow2[abs(hi-center[1])] <= r:
+                    poly.add((wi, hi))
+        self.components.append(poly)
+        return poly
+    def rotate_component(comp, radian):
+        retv = set()
+        return retv
+    def save(self):
+        Image.fromarray(self.img1).filter(filter=ImageFilter.GaussianBlur(random.randint(0, 1))).save(self.file_name)
+        Image.fromarray(self.img2).save(self.depth_name)
+        with open(self.tags_name, "w") as file:
+            if self.layer_max is None:
+                file.write("")
+            else:
+                file.write(f"{self.layer_max+1}depth")
+
+    
+import uuid
+import concurrent.futures
+from tqdm import tqdm
+import os
+
+def process_polygon():
+    random_uuid = str(uuid.uuid4())
+    polygon = SimplePolygon(f"data/{random_uuid}.png", f"label/{random_uuid}.png", f"data/{random_uuid}.txt")
+    for _ in range(random.randint(4, 10)):
+        if random.randint(0,1)==0:
+            polygon.add_ellipse()
+        else:
+            polygon.add_rect()
+    polygon.generate()
+    polygon.save()
+
+def main():
+    if not os.path.exists("data"):
+        os.makedirs("data")
+    if not os.path.exists("label"):
+        os.makedirs("label")
+    num_processes = 12 
+    total_runs = 100000 
+
+    with tqdm(total=total_runs, ncols=80) as pbar:
+        with concurrent.futures.ProcessPoolExecutor(max_workers=num_processes) as executor:
+            futures = [executor.submit(process_polygon) for _ in range(total_runs)]
+            for future in concurrent.futures.as_completed(futures):
+                pbar.update(1)
+
+if __name__ == "__main__":
+    main()

label.zip

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+version https://git-lfs.github.com/spec/v1
+oid sha256:092fdbfed30fc966b07739ad3f87646a58a018d9112e1675e066cbc269b83d93
+size 298943046

readme.md

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+
+
+
+# depth(?) overlap TrainData
+
+Approximately 100,000 images
+
+## example 1
+
+![example 1 train](sample/000adad0-657b-4ce4-93d2-159f3ca80798.png)
+
+
+![example 1 label](sample/000adad0-657b-4ce4-93d2-159f3ca80798-label.png)
+
+## example 2
+
+![example 2 train](sample/0000c1cd-30d9-42e8-82ae-9109ca6be939.png)
+
+
+![example 2 label](sample/0000c1cd-30d9-42e8-82ae-9109ca6be939-label.png)
+

sample/0000c1cd-30d9-42e8-82ae-9109ca6be939.txt

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+5depth

sample/000adad0-657b-4ce4-93d2-159f3ca80798.txt

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+5depth