Initial commit

ML/TensorFlow/Basics/tutorial20-classify-cancer-beginner-project-example/process_data.py

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+import os
+import shutil
+import random
+
+seed = 1
+random.seed(seed)
+directory = "ISIC/images/"
+train = "data/train/"
+test = "data/test/"
+validation = "data/validation/"
+
+os.makedirs(train + "benign/")
+os.makedirs(train + "malignant/")
+os.makedirs(test + "benign/")
+os.makedirs(test + "malignant/")
+os.makedirs(validation + "benign/")
+os.makedirs(validation + "malignant/")
+
+test_examples = train_examples = validation_examples = 0
+
+for line in open("ISIC/labels.csv").readlines()[1:]:
+    split_line = line.split(",")
+    img_file = split_line[0]
+    benign_malign = split_line[1]
+
+    random_num = random.random()
+
+    if random_num < 0.8:
+        location = train
+        train_examples += 1
+
+    elif random_num < 0.9:
+        location = validation
+        validation_examples += 1
+
+    else:
+        location = test
+        test_examples += 1
+
+    if int(float(benign_malign)) == 0:
+        shutil.copy(
+            "ISIC/images/" + img_file + ".jpg",
+            location + "benign/" + img_file + ".jpg",
+        )
+
+    elif int(float(benign_malign)) == 1:
+        shutil.copy(
+            "ISIC/images/" + img_file + ".jpg",
+            location + "malignant/" + img_file + ".jpg",
+        )
+
+print(f"Number of training examples {train_examples}")
+print(f"Number of test examples {test_examples}")
+print(f"Number of validation examples {validation_examples}")