diff --git a/Code/Ball_Detection/TFLite-1/ball-detection-model.tflite b/Code/Ball_Detection/TFLite-1/ball-detection-model.tflite
new file mode 100644
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diff --git a/Code/Ball_Detection/TFLite-1/ball-detection-tflite.py b/Code/Ball_Detection/TFLite-1/ball-detection-tflite.py
new file mode 100644
index 0000000000000000000000000000000000000000..3b3695c79e334aa8b85e9b6bf14940cb6a9af1b7
--- /dev/null
+++ b/Code/Ball_Detection/TFLite-1/ball-detection-tflite.py
@@ -0,0 +1,155 @@
+import os
+import cv2
+import numpy as np
+import tensorflow as tf
+
+from PIL import Image
+from absl import logging
+from tflite_model_maker import model_spec
+from tflite_model_maker.config import ExportFormat
+from tflite_model_maker.object_detector import create, DataLoader
+
+assert tf.__version__.startswith('2')
+tf.get_logger().setLevel('ERROR')
+logging.set_verbosity(logging.ERROR)
+
+spec = model_spec.get('efficientdet_lite0')
+
+train_data = DataLoader.from_pascal_voc('../images/train-test-2/train/images',
+ '../images/train-test-2/train/annotations',
+ label_map = {1: 'ball'})
+validation_data = DataLoader.from_pascal_voc('../images/train-test-2/validation/images',
+ '../images/train-test-2/validation/annotations',
+ label_map = {1: 'ball'})
+test_data = DataLoader.from_pascal_voc('../images/train-test-2/test/images',
+ '../images/train-test-2/test/annotations',
+ label_map = {1: 'ball'})
+
+model = create(train_data, model_spec = spec, batch_size = 8, train_whole_model = True, validation_data = validation_data)
+
+model.evaluate(test_data)
+
+model.export(export_dir='.',
+ tflite_filename = 'ball-detection-model.tflite',
+ label_filename = 'ball-detection-labels.txt',
+ vocab_filename = 'ball-detection-vocab.txt',
+ saved_model_filename = 'saved_ball-detection-model')
+
+model.evaluate_tflite('ball-detection-model.tflite', test_data)
+
+model_path = 'ball-detection-model.tflite'
+INPUT_IMAGE_URL = "../images/train-test-2/test/images/036.jpg"
+DETECTION_THRESHOLD = 0.75
+
+# Load the labels into a list
+classes = ['???'] * model.model_spec.config.num_classes
+label_map = model.model_spec.config.label_map
+for label_id, label_name in label_map.as_dict().items():
+ classes[label_id-1] = label_name
+
+# Define a list of colors for visualization
+COLORS = np.random.randint(0, 255, size=(len(classes), 3), dtype=np.uint8)
+
+def preprocess_image(image_path, input_size):
+ """Preprocess the input image to feed to the TFLite model"""
+ img = tf.io.read_file(image_path)
+ img = tf.io.decode_image(img, channels=3)
+ img = tf.image.convert_image_dtype(img, tf.uint8)
+ original_image = img
+ resized_img = tf.image.resize(img, input_size)
+ resized_img = resized_img[tf.newaxis, :]
+ return resized_img, original_image
+
+def set_input_tensor(interpreter, image):
+ """Set the input tensor."""
+ tensor_index = interpreter.get_input_details()[0]['index']
+ input_tensor = interpreter.tensor(tensor_index)()[0]
+ input_tensor[:, :] = image
+
+def get_output_tensor(interpreter, index):
+ """Retur the output tensor at the given index."""
+ output_details = interpreter.get_output_details()[index]
+ tensor = np.squeeze(interpreter.get_tensor(output_details['index']))
+ return tensor
+
+def detect_objects(interpreter, image, threshold):
+ """Returns a list of detection results, each a dictionary of object info."""
+ # Feed the input image to the model
+ set_input_tensor(interpreter, image)
+ interpreter.invoke()
+
+ # Get all outputs from the model
+ boxes = get_output_tensor(interpreter, 0)
+ classes = get_output_tensor(interpreter, 1)
+ scores = get_output_tensor(interpreter, 2)
+ count = int(get_output_tensor(interpreter, 3))
+
+ results = []
+ for i in range(count):
+ if scores[i] >= threshold:
+ result = {
+ 'bounding_box': boxes[i],
+ 'class_id': classes[i],
+ 'score': scores[i]
+ }
+ results.append(result)
+ return results
+
+def run_odt_and_draw_results(image_path, interpreter, threshold=0.5):
+ """Run object detection on the input image and draw the detection results"""
+ # Load the input shape required by the model
+ _, input_height, input_width, _ = interpreter.get_input_details()[0]['shape']
+
+ # Load the input image and preprocess it
+ preprocessed_image, original_image = preprocess_image(
+ image_path,
+ (input_height, input_width)
+ )
+
+ # Run object detection on the input image
+ results = detect_objects(interpreter, preprocessed_image, threshold=threshold)
+
+ # Plot the detection results on the input image
+ original_image_np = original_image.numpy().astype(np.uint8)
+ for obj in results:
+ # Convert the object bounding box from relative coordinates to absolute
+ # coordinates based on the original image resolution
+ ymin, xmin, ymax, xmax = obj['bounding_box']
+ xmin = int(xmin * original_image_np.shape[1])
+ xmax = int(xmax * original_image_np.shape[1])
+ ymin = int(ymin * original_image_np.shape[0])
+ ymax = int(ymax * original_image_np.shape[0])
+
+ # Find the class index of the current object
+ class_id = int(obj['class_id'])
+
+ # Draw the bounding box and label on the image
+ color = [int(c) for c in COLORS[class_id]]
+ cv2.rectangle(original_image_np, (xmin, ymin), (xmax, ymax), color, 2)
+ # Make adjustments to make the label visible for all objects
+ y = ymin - 15 if ymin - 15 > 15 else ymin + 15
+ label = "{}: {:.0f}%".format(classes[class_id], obj['score'] * 100)
+ cv2.putText(original_image_np, label, (xmin, y),
+ cv2.FONT_HERSHEY_SIMPLEX, 0.5, color, 2)
+
+ # Return the final image
+ original_uint8 = original_image_np.astype(np.uint8)
+ return original_uint8
+
+im = Image.open(INPUT_IMAGE_URL)
+im.thumbnail((512, 512), Image.ANTIALIAS)
+im.save(INPUT_IMAGE_URL, 'PNG')
+
+# Load the TFLite model
+interpreter = tf.lite.Interpreter(model_path=model_path)
+interpreter.allocate_tensors()
+
+# Run inference and draw detection result on the local copy of the original file
+detection_result_image = run_odt_and_draw_results(
+ INPUT_IMAGE_URL,
+ interpreter,
+ threshold=DETECTION_THRESHOLD
+)
+
+# Show the detection result
+Image.fromarray(detection_result_image)
\ No newline at end of file
diff --git a/Code/Ball_Detection/TFLite-1/flowers-classification-model.tflite b/Code/Ball_Detection/TFLite-1/flowers-classification-model.tflite
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index 0000000000000000000000000000000000000000..dfdb8d1d0b970de34b48b85cf79b9983b5dfb48e
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diff --git a/Code/Ball_Detection/TFLite-1/flowers-classification-tflite.py b/Code/Ball_Detection/TFLite-1/flowers-classification-tflite.py
new file mode 100644
index 0000000000000000000000000000000000000000..69042bce64f79ab3f381e4417067b3d52a85e765
--- /dev/null
+++ b/Code/Ball_Detection/TFLite-1/flowers-classification-tflite.py
@@ -0,0 +1,49 @@
+import os
+
+import numpy as np
+
+import tensorflow as tf
+assert tf.__version__.startswith('2')
+
+from tflite_model_maker import model_spec
+from tflite_model_maker import image_classifier
+from tflite_model_maker.config import ExportFormat
+from tflite_model_maker.config import QuantizationConfig
+from tflite_model_maker.image_classifier import DataLoader
+
+import matplotlib.pyplot as plt
+
+image_path = tf.keras.utils.get_file(
+ 'flower_photos.tgz',
+ 'https://storage.googleapis.com/download.tensorflow.org/example_images/flower_photos.tgz',
+ extract=True)
+image_path = os.path.join(os.path.dirname(image_path), 'flower_photos')
+
+data = DataLoader.from_folder(image_path)
+train_data, rest_data = data.split(0.8)
+validation_data, test_data = rest_data.split(0.5)
+
+model = image_classifier.create(train_data, validation_data=validation_data)
+
+model.summary()
+
+loss, accuracy = model.evaluate(test_data)
+
+model.export(export_dir='.',
+ tflite_filename='flowers-classification-model.tflite',
+ label_filename='flowers-classification-labels.txt',
+ vocab_filename='flowers-classification-vocab.txt',
+ saved_model_filename='saved_flowers-classification-model')
+
+model.evaluate_tflite('flowers-classification-model.tflite', test_data)
+
+plt.figure(figsize=(10,10))
+for i, (image, label) in enumerate(data.gen_dataset().unbatch().take(25)):
+ plt.subplot(5,5,i+1)
+ plt.xticks([])
+ plt.yticks([])
+ plt.grid(False)
+ plt.imshow(image.numpy(), cmap=plt.cm.gray)
+ plt.xlabel(data.index_to_label[label.numpy()])
+plt.show()
+
diff --git a/Code/Ball_Detection/TFLite-2/ball-detection-tflite.py b/Code/Ball_Detection/TFLite-2/ball-detection-tflite.py
new file mode 100644
index 0000000000000000000000000000000000000000..92ede401544c019bba1bfffee18cd7998fa5d520
--- /dev/null
+++ b/Code/Ball_Detection/TFLite-2/ball-detection-tflite.py
@@ -0,0 +1,34 @@
+# Taken from https://github.com/NSTiwari/Custom-Object-Detection-on-Android-using-TF-Lite/blob/master/Custom_Object_Detection_using_TF_Lite_Model_Maker.ipynb
+
+import numpy as np
+import os
+import glob
+import PIL.Image
+
+from tflite_model_maker.config import ExportFormat
+from tflite_model_maker import model_spec
+from tflite_model_maker import object_detector
+
+import tensorflow as tf
+assert tf.__version__.startswith('2')
+
+tf.get_logger().setLevel('ERROR')
+from absl import logging
+logging.set_verbosity(logging.ERROR)
+
+img = PIL.Image.open('/content/cartoon-detection/train/images/cartoon57.jpg')
+img.format
+
+spec = model_spec.get('efficientdet_lite2')
+
+train_data = object_detector.DataLoader.from_pascal_voc("/content/cartoon-detection/train/images", "/content/cartoon-detection/train/annotations", ['doraemon', 'mrbean', 'scooby', 'mickey', 'mcqueen'])
+
+validation_data = object_detector.DataLoader.from_pascal_voc('cartoon-detection/test/images', 'cartoon-detection/test/annotations', ['doraemon', 'mrbean', 'scooby', 'mickey', 'mcqueen'])
+
+model = object_detector.create(train_data, model_spec=spec, batch_size=4, train_whole_model=True, validation_data=validation_data)
+
+model.evaluate(validation_data)
+
+model.export(export_dir='.')
+
+model.evaluate_tflite('model.tflite', validation_data)
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+ <path>G:\Shared drives\ECE 209 Blimp project\Color Segmentation\images\training-images\test\008.jpg</path>
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+ <path>G:\Shared drives\ECE 209 Blimp project\Color Segmentation\images\training-images\train\009.jpg</path>
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+ <path>G:\Shared drives\ECE 209 Blimp project\Color Segmentation\images\training-images\train\010.jpg</path>
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+ <path>G:\Shared drives\ECE 209 Blimp project\Color Segmentation\images\training-images\train\011.jpg</path>
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new file mode 100644
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@@ -0,0 +1,26 @@
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+ <folder>train</folder>
+ <filename>029.jpg</filename>
+ <path>G:\Shared drives\ECE 209 Blimp project\Color Segmentation\images\training-images\train\029.jpg</path>
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+ <size>
+ <width>1920</width>
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@@ -0,0 +1,38 @@
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+ <folder>train</folder>
+ <filename>030.jpg</filename>
+ <path>G:\Shared drives\ECE 209 Blimp project\Color Segmentation\images\training-images\train\030.jpg</path>
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+ <size>
+ <width>1280</width>
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+<annotation>
+ <folder>train</folder>
+ <filename>031.jpg</filename>
+ <path>G:\Shared drives\ECE 209 Blimp project\Color Segmentation\images\training-images\train\031.jpg</path>
+ <source>
+ <database>Unknown</database>
+ </source>
+ <size>
+ <width>1920</width>
+ <height>1080</height>
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+<annotation>
+ <folder>train</folder>
+ <filename>033.jpg</filename>
+ <path>G:\Shared drives\ECE 209 Blimp project\Color Segmentation\images\training-images\train\033.jpg</path>
+ <source>
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+ </source>
+ <size>
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+<annotation>
+ <folder>train</folder>
+ <filename>034.jpg</filename>
+ <path>G:\Shared drives\ECE 209 Blimp project\Color Segmentation\images\training-images\train\034.jpg</path>
+ <source>
+ <database>Unknown</database>
+ </source>
+ <size>
+ <width>1280</width>
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+ </bndbox>
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+ <filename>035.jpg</filename>
+ <path>G:\Shared drives\ECE 209 Blimp project\Color Segmentation\images\training-images\train\035.jpg</path>
+ <source>
+ <database>Unknown</database>
+ </source>
+ <size>
+ <width>1280</width>
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+ <folder>train</folder>
+ <filename>037.jpg</filename>
+ <path>G:\Shared drives\ECE 209 Blimp project\Color Segmentation\images\training-images\train\037.jpg</path>
+ <source>
+ <database>Unknown</database>
+ </source>
+ <size>
+ <width>1280</width>
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+<annotation>
+ <folder>train</folder>
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+ <path>G:\Shared drives\ECE 209 Blimp project\Color Segmentation\images\training-images\train\038.jpg</path>
+ <source>
+ <database>Unknown</database>
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+ <size>
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+<annotation>
+ <folder>train</folder>
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+ <database>Unknown</database>
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+ <size>
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+<annotation>
+ <folder>train</folder>
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+ <path>G:\Shared drives\ECE 209 Blimp project\Color Segmentation\images\training-images\train\041.jpg</path>
+ <source>
+ <database>Unknown</database>
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+ <size>
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+ <path>G:\Shared drives\ECE 209 Blimp project\Color Segmentation\images\training-images\train\042.jpg</path>
+ <source>
+ <database>Unknown</database>
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+ <size>
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+<annotation>
+ <folder>train</folder>
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+ <path>G:\Shared drives\ECE 209 Blimp project\Color Segmentation\images\training-images\train\043.jpg</path>
+ <source>
+ <database>Unknown</database>
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+ <size>
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+ <folder>train</folder>
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+ <path>G:\Shared drives\ECE 209 Blimp project\Color Segmentation\images\training-images\train\045.jpg</path>
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+ <database>Unknown</database>
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+ <size>
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+ <path>G:\Shared drives\ECE 209 Blimp project\Color Segmentation\images\training-images\train\047.jpg</path>
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new file mode 100644
index 0000000000000000000000000000000000000000..af2116ed48d2daa7d77d5ecf21d3551af4b4dcaa
--- /dev/null
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@@ -0,0 +1,38 @@
+<annotation>
+ <folder>train</folder>
+ <filename>049.jpg</filename>
+ <path>G:\Shared drives\ECE 209 Blimp project\Color Segmentation\images\training-images\train\049.jpg</path>
+ <source>
+ <database>Unknown</database>
+ </source>
+ <size>
+ <width>1024</width>
+ <height>768</height>
+ <depth>3</depth>
+ </size>
+ <segmented>0</segmented>
+ <object>
+ <name>ball</name>
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+ <difficult>0</difficult>
+ <bndbox>
+ <xmin>233</xmin>
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+ <xmax>499</xmax>
+ <ymax>551</ymax>
+ </bndbox>
+ </object>
+ <object>
+ <name>ball</name>
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+ <ymax>608</ymax>
+ </bndbox>
+ </object>
+</annotation>
diff --git a/Code/Ball_Detection/images/train-test-2/train/annotations/050.xml b/Code/Ball_Detection/images/train-test-2/train/annotations/050.xml
new file mode 100644
index 0000000000000000000000000000000000000000..713fd5f20ee39c3d61b05932c0dd457e31544894
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+<annotation>
+ <folder>train</folder>
+ <filename>050.jpg</filename>
+ <path>G:\Shared drives\ECE 209 Blimp project\Color Segmentation\images\training-images\train\050.jpg</path>
+ <source>
+ <database>Unknown</database>
+ </source>
+ <size>
+ <width>1024</width>
+ <height>768</height>
+ <depth>3</depth>
+ </size>
+ <segmented>0</segmented>
+ <object>
+ <name>ball</name>
+ <pose>Unspecified</pose>
+ <truncated>0</truncated>
+ <difficult>0</difficult>
+ <bndbox>
+ <xmin>642</xmin>
+ <ymin>341</ymin>
+ <xmax>968</xmax>
+ <ymax>640</ymax>
+ </bndbox>
+ </object>
+ <object>
+ <name>ball</name>
+ <pose>Unspecified</pose>
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+ <difficult>0</difficult>
+ <bndbox>
+ <xmin>483</xmin>
+ <ymin>495</ymin>
+ <xmax>757</xmax>
+ <ymax>756</ymax>
+ </bndbox>
+ </object>
+</annotation>
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new file mode 100644
index 0000000000000000000000000000000000000000..a8cd17bff4678096995001ac23ce526d7815bdcc
--- /dev/null
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@@ -0,0 +1,38 @@
+<annotation>
+ <folder>train</folder>
+ <filename>051.jpg</filename>
+ <path>G:\Shared drives\ECE 209 Blimp project\Color Segmentation\images\training-images\train\051.jpg</path>
+ <source>
+ <database>Unknown</database>
+ </source>
+ <size>
+ <width>1280</width>
+ <height>1080</height>
+ <depth>3</depth>
+ </size>
+ <segmented>0</segmented>
+ <object>
+ <name>ball</name>
+ <pose>Unspecified</pose>
+ <truncated>0</truncated>
+ <difficult>0</difficult>
+ <bndbox>
+ <xmin>774</xmin>
+ <ymin>155</ymin>
+ <xmax>931</xmax>
+ <ymax>345</ymax>
+ </bndbox>
+ </object>
+ <object>
+ <name>ball</name>
+ <pose>Unspecified</pose>
+ <truncated>0</truncated>
+ <difficult>0</difficult>
+ <bndbox>
+ <xmin>654</xmin>
+ <ymin>569</ymin>
+ <xmax>794</xmax>
+ <ymax>725</ymax>
+ </bndbox>
+ </object>
+</annotation>
diff --git a/Code/Ball_Detection/images/train-test-2/train/annotations/053.xml b/Code/Ball_Detection/images/train-test-2/train/annotations/053.xml
new file mode 100644
index 0000000000000000000000000000000000000000..6db884064978d0302c6d2fc6a2541fdeba85ec4f
--- /dev/null
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+<annotation>
+ <folder>train</folder>
+ <filename>053.jpg</filename>
+ <path>G:\Shared drives\ECE 209 Blimp project\Color Segmentation\images\training-images\train\053.jpg</path>
+ <source>
+ <database>Unknown</database>
+ </source>
+ <size>
+ <width>1024</width>
+ <height>768</height>
+ <depth>3</depth>
+ </size>
+ <segmented>0</segmented>
+ <object>
+ <name>ball</name>
+ <pose>Unspecified</pose>
+ <truncated>0</truncated>
+ <difficult>0</difficult>
+ <bndbox>
+ <xmin>552</xmin>
+ <ymin>258</ymin>
+ <xmax>861</xmax>
+ <ymax>553</ymax>
+ </bndbox>
+ </object>
+ <object>
+ <name>ball</name>
+ <pose>Unspecified</pose>
+ <truncated>0</truncated>
+ <difficult>0</difficult>
+ <bndbox>
+ <xmin>381</xmin>
+ <ymin>341</ymin>
+ <xmax>629</xmax>
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+ </bndbox>
+ </object>
+</annotation>
diff --git a/Code/Ball_Detection/images/train-test-2/train/annotations/054.xml b/Code/Ball_Detection/images/train-test-2/train/annotations/054.xml
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index 0000000000000000000000000000000000000000..17ee2b3e344aa4b6c20bc22962d037962ff54d9c
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+<annotation>
+ <folder>train</folder>
+ <filename>054.jpg</filename>
+ <path>G:\Shared drives\ECE 209 Blimp project\Color Segmentation\images\training-images\train\054.jpg</path>
+ <source>
+ <database>Unknown</database>
+ </source>
+ <size>
+ <width>1280</width>
+ <height>1080</height>
+ <depth>3</depth>
+ </size>
+ <segmented>0</segmented>
+ <object>
+ <name>ball</name>
+ <pose>Unspecified</pose>
+ <truncated>0</truncated>
+ <difficult>0</difficult>
+ <bndbox>
+ <xmin>743</xmin>
+ <ymin>310</ymin>
+ <xmax>1131</xmax>
+ <ymax>726</ymax>
+ </bndbox>
+ </object>
+ <object>
+ <name>ball</name>
+ <pose>Unspecified</pose>
+ <truncated>0</truncated>
+ <difficult>0</difficult>
+ <bndbox>
+ <xmin>655</xmin>
+ <ymin>572</ymin>
+ <xmax>796</xmax>
+ <ymax>721</ymax>
+ </bndbox>
+ </object>
+</annotation>
diff --git a/Code/Ball_Detection/images/train-test-2/train/annotations/055.xml b/Code/Ball_Detection/images/train-test-2/train/annotations/055.xml
new file mode 100644
index 0000000000000000000000000000000000000000..96fe33203cb57558990101ae2874f34c59033182
--- /dev/null
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+<annotation>
+ <folder>train</folder>
+ <filename>055.jpg</filename>
+ <path>G:\Shared drives\ECE 209 Blimp project\Color Segmentation\images\training-images\train\055.jpg</path>
+ <source>
+ <database>Unknown</database>
+ </source>
+ <size>
+ <width>1280</width>
+ <height>1080</height>
+ <depth>3</depth>
+ </size>
+ <segmented>0</segmented>
+ <object>
+ <name>ball</name>
+ <pose>Unspecified</pose>
+ <truncated>0</truncated>
+ <difficult>0</difficult>
+ <bndbox>
+ <xmin>512</xmin>
+ <ymin>246</ymin>
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+ <ymax>387</ymax>
+ </bndbox>
+ </object>
+ <object>
+ <name>ball</name>
+ <pose>Unspecified</pose>
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+ <bndbox>
+ <xmin>742</xmin>
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+ </bndbox>
+ </object>
+</annotation>
diff --git a/Code/Ball_Detection/images/train-test-2/train/annotations/057.xml b/Code/Ball_Detection/images/train-test-2/train/annotations/057.xml
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index 0000000000000000000000000000000000000000..5c8b73f0f5c23994e476c8b82665e8b5c54fda07
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+<annotation>
+ <folder>train</folder>
+ <filename>057.jpg</filename>
+ <path>G:\Shared drives\ECE 209 Blimp project\Color Segmentation\images\training-images\train\057.jpg</path>
+ <source>
+ <database>Unknown</database>
+ </source>
+ <size>
+ <width>1280</width>
+ <height>1080</height>
+ <depth>3</depth>
+ </size>
+ <segmented>0</segmented>
+ <object>
+ <name>ball</name>
+ <pose>Unspecified</pose>
+ <truncated>1</truncated>
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+ <bndbox>
+ <xmin>645</xmin>
+ <ymin>1</ymin>
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+ <ymax>466</ymax>
+ </bndbox>
+ </object>
+ <object>
+ <name>ball</name>
+ <pose>Unspecified</pose>
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+ <xmin>811</xmin>
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+ </bndbox>
+ </object>
+</annotation>
diff --git a/Code/Ball_Detection/images/train-test-2/train/annotations/058.xml b/Code/Ball_Detection/images/train-test-2/train/annotations/058.xml
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+<annotation>
+ <folder>train</folder>
+ <filename>058.jpg</filename>
+ <path>G:\Shared drives\ECE 209 Blimp project\Color Segmentation\images\training-images\train\058.jpg</path>
+ <source>
+ <database>Unknown</database>
+ </source>
+ <size>
+ <width>1280</width>
+ <height>1080</height>
+ <depth>3</depth>
+ </size>
+ <segmented>0</segmented>
+ <object>
+ <name>ball</name>
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+ <bndbox>
+ <xmin>86</xmin>
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+ <ymax>560</ymax>
+ </bndbox>
+ </object>
+ <object>
+ <name>ball</name>
+ <pose>Unspecified</pose>
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+ <bndbox>
+ <xmin>984</xmin>
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+ </bndbox>
+ </object>
+</annotation>
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@@ -0,0 +1,38 @@
+<annotation>
+ <folder>train</folder>
+ <filename>059.jpg</filename>
+ <path>G:\Shared drives\ECE 209 Blimp project\Color Segmentation\images\training-images\train\059.jpg</path>
+ <source>
+ <database>Unknown</database>
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+ <size>
+ <width>1280</width>
+ <height>1080</height>
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+ </size>
+ <segmented>0</segmented>
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+ <bndbox>
+ <xmin>414</xmin>
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+ <ymax>515</ymax>
+ </bndbox>
+ </object>
+ <object>
+ <name>ball</name>
+ <pose>Unspecified</pose>
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+ <bndbox>
+ <xmin>690</xmin>
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+ </object>
+</annotation>
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+<annotation>
+ <folder>train</folder>
+ <filename>071.jpg</filename>
+ <path>G:\Shared drives\ECE 209 Blimp project\Color Segmentation\images\training-images\train\071.jpg</path>
+ <source>
+ <database>Unknown</database>
+ </source>
+ <size>
+ <width>1280</width>
+ <height>1080</height>
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+ </size>
+ <segmented>0</segmented>
+ <object>
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+ <ymax>998</ymax>
+ </bndbox>
+ </object>
+ <object>
+ <name>ball</name>
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+ <bndbox>
+ <xmin>349</xmin>
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+ </object>
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+<annotation>
+ <folder>train</folder>
+ <filename>073.jpg</filename>
+ <path>G:\Shared drives\ECE 209 Blimp project\Color Segmentation\images\training-images\train\073.jpg</path>
+ <source>
+ <database>Unknown</database>
+ </source>
+ <size>
+ <width>1280</width>
+ <height>1080</height>
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+ <object>
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+ </bndbox>
+ </object>
+</annotation>
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new file mode 100644
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+<annotation>
+ <folder>train</folder>
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+ <path>G:\Shared drives\ECE 209 Blimp project\Color Segmentation\images\training-images\train\074.jpg</path>
+ <source>
+ <database>Unknown</database>
+ </source>
+ <size>
+ <width>1280</width>
+ <height>1080</height>
+ <depth>3</depth>
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+ <object>
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+ </object>
+ <object>
+ <name>ball</name>
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+ </bndbox>
+ </object>
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diff --git a/Code/Ball_Detection/images/train-test-2/train/annotations/075.xml b/Code/Ball_Detection/images/train-test-2/train/annotations/075.xml
new file mode 100644
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+<annotation>
+ <folder>train</folder>
+ <filename>075.jpg</filename>
+ <path>G:\Shared drives\ECE 209 Blimp project\Color Segmentation\images\training-images\train\075.jpg</path>
+ <source>
+ <database>Unknown</database>
+ </source>
+ <size>
+ <width>1024</width>
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+ </object>
+ <object>
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+ </bndbox>
+ </object>
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diff --git a/Code/Ball_Detection/images/train-test-2/train/annotations/077.xml b/Code/Ball_Detection/images/train-test-2/train/annotations/077.xml
new file mode 100644
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+<annotation>
+ <folder>train</folder>
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+ <path>G:\Shared drives\ECE 209 Blimp project\Color Segmentation\images\training-images\train\077.jpg</path>
+ <source>
+ <database>Unknown</database>
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+ <size>
+ <width>1280</width>
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+ <segmented>0</segmented>
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+ <object>
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+ </bndbox>
+ </object>
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new file mode 100644
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+<annotation>
+ <folder>train</folder>
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+ <path>G:\Shared drives\ECE 209 Blimp project\Color Segmentation\images\training-images\train\078.jpg</path>
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+ <database>Unknown</database>
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+ <size>
+ <width>1280</width>
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+ <object>
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diff --git a/Code/Ball_Detection/images/train-test-2/train/annotations/079.xml b/Code/Ball_Detection/images/train-test-2/train/annotations/079.xml
new file mode 100644
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+<annotation>
+ <folder>train</folder>
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+ <path>G:\Shared drives\ECE 209 Blimp project\Color Segmentation\images\training-images\train\079.jpg</path>
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+ <database>Unknown</database>
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+ <size>
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