pranjalsatija

import os
import turicreate as tc
import xml.etree.cElementTree as XMLParser


# Takes the XML for a bounding box and returns a Dictionary containing the center X and Y coordinates of the box,
# along with its width and height.
def get_bounding_box(xml):
    box = xml.find('bndbox')
    x_min, x_max = float(box.find('xmin').text), float(box.find('xmax').text)

pranjalsatija

import os
import turicreate as tc

path = '../'  # The path to the root of your project directory.
sf_path = os.path.join(path, 'data.sframe')  # The path to load the SFrame from. See `gen_sframe.py` for more.
data = tc.SFrame(sf_path)  # The training data for our model.

# This takes the first 50 rows from the SFrame we just loaded from disk and drops the rest of it. We do this so the
# visualization doesn't take too long to load and run.
data = data.head(50)

pranjalsatija

import os
import turicreate as tc

path = '../'  # The path to the root of your project directory.
coreml_path = os.path.join(path, 'pascal.mlmodel')  # The path to export the Core ML model to.
model_path = os.path.join(path, 'pascal.model')  # The path to export the .model file to.
sf_path = os.path.join(path, 'data.sframe')  # The path to load the SFrame from. See gen_sframe.py for more.
result_sf_path = os.path.join(path, 'result_data.sframe')  # The path to save the test data with predictions to.
data = tc.SFrame(sf_path)  # The training data for our model.

pranjalsatija

import os
import turicreate as tc

path = '../'  # The path to the root of your project directory.
model_path = os.path.join(path, 'pascal.model')  # The path to the trained model. See train_model.py for more.
result_sf_path = os.path.join(path, 'result_data.sframe')  # The path to the result data from training the model.

# Loads the result data from training the model, along with the model itself.
data = tc.SFrame(result_sf_path)
model = tc.load_model(model_path)

pranjalsatija

pranjal:app $ flutter run --verbose
[  +35 ms] executing: [/Users/pranjal/flutter/] git log -n 1 --pretty=format:%H
[  +41 ms] Exit code 0 from: git log -n 1 --pretty=format:%H
[        ] 7a4c33425ddd78c54aba07d86f3f9a4a0051769b
[        ] executing: [/Users/pranjal/flutter/] git describe --match v*.*.* --first-parent --long --tags
[  +18 ms] Exit code 0 from: git describe --match v*.*.* --first-parent --long --tags
[        ] v1.5.4-hotfix.2-0-g7a4c33425
[  +14 ms] executing: [/Users/pranjal/flutter/] git rev-parse --abbrev-ref --symbolic @{u}
[  +11 ms] Exit code 0 from: git rev-parse --abbrev-ref --symbolic @{u}
[        ] origin/stable

pranjalsatija

List(data, id: \.self) {
    Text($0)
}

pranjalsatija

class UITableViewCoordinator: UITableViewDataSource, UITableViewDelegate {
    func tableView(_ tableView: UITableView, numberOfRowsInSection section: Int) -> Int {
        data.count
    }
    
    func tableView(_ tableView: UITableView, cellForRowAt indexPath: IndexPath) -> UITableViewCell {
        let cell = tableView.dequeueReusableCell(withIdentifier: "identifier") as! Cell
        // configure it
        return cell
    }

pranjalsatija

let dataSource = DataSource()
dataSource.sections = [
    Section(rows: [
        Row(text: "Hello")
    ])
]

dataSource.tableView = tableView

pranjalsatija

tableView.descriptor = UITableViewDescriptor(sections: [
    UITableViewSection(
        items: $data,
        cellProvider: {(tableView, indexPath, element) in
            let cell = Cell.dequeue(in: tableView)
            cell.configure(with: element)
            return cell
        }
    )

pranjalsatija

class UITableViewSection: NSObject {
    private(set) var items = [AnyHashable]()
    private(set) var sectionIndex: Int!
    
    private let itemsPublisher: AnyPublisher<[AnyHashable], Never>
    private let cellProvider: (UITableView, IndexPath, AnyHashable) -> UITableViewCell
    
    private var subscriptions = Set<AnyCancellable>()
    
    convenience init<T: Hashable>(