def write():
udisp.title_awesome("Resources")
image = Image.open('./img/2.jfif')
st.image(image, use_column_width=True)
keys = {'Videos', 'Datasets', 'Articles', 'Publications', 'Citations'}
pick = st.selectbox("Select An Option", list(keys))
if pick == 'Datasets':
udisp.render_md("resources/datasets.md")
elif pick == 'Videos':
udisp.render_md("resources/videos.md")
elif pick == 'Articles':
udisp.render_md("resources/articles.md")
elif pick == 'Publications':
udisp.render_md("resources/publications.md")
elif pick == 'Citations':
udisp.render_md("resources/citations.md")
def write():
#st.title("Summarize URL")
summaryurleng.sumurl_main("Summarize URL", "Enter or paste url in the below box")
udisp.render_md("resources/summaryurl2.md")
udisp.render_md("resources/summaryurl.md")
# if st.checkbox("Show help document"):
# st.code(udisp.render_md("resources/summaryurl.md"))
def write():
udisp.title_awesome("3D Photo Creator")
video_keys = globalDefine.SAMPLE_VIDEO_LIST.keys()
video_id = st.selectbox("Select a sample 3D video output ",
list(video_keys))
video_choice = globalDefine.SAMPLE_VIDEO_LIST.get(video_id)
st.video(video_choice, format='video/mp4', start_time=0)
udisp.render_md("resources/home_info.md")
def write():
st.image(image,
caption=None,
width=None,
use_column_width=True,
clamp=False,
channels='RGB')
#st.title("Automated Summary App")
udisp.render_md("resources/home_info.md")
def calc_main(title, subtitle):
st.sidebar.title(title)
st.sidebar.info(subtitle)
if st.checkbox("Show help document? "):
display.render_md("resources/compound.md")
show_operator = False
principal_float = st.text_input('Please input principal amound: ')
rate_float = st.text_input('Please input annual interest rate (float): ')
years_float = st.text_input('Please input years (float): ')
m_y_keys = globalDefine.CI_CHOICE.keys()
m_y_id = st.selectbox("Select Compound Option (Monthly/Yearly): ",
list(m_y_keys))
monthly_yearly = globalDefine.CI_CHOICE.get(m_y_id)
if not principal_float.isnumeric() and not rate_float.isnumeric(
) and not years_float.isnumeric():
st.write("Principal, rate & years must be numeric")
else:
P = float(principal_float)
R = float(rate_float)
N = float(years_float)
show_operator = True
if show_operator:
if (monthly_yearly == "YEARLY"):
st.write("Formula: " + "CI = P * (pow((1 + R / 100), N)) ")
CI = yearly_compound_interest(P, R, N)
st.write(
'At the end of ', N,
'year(s) your principal plus compound interest will be $',
format(CI, '.2f'))
else:
st.write("Formula: " + "CI = P * (1 + R / 12) ** (12 * T)")
st.write(
"Note: For montly compound interst the rate is divided by 100 means R = R/100"
)
CI = monthly_compound_interest(P, R / 100, N)
st.write(
'At the end of ', N,
'year(s) your principal plus compound interest will be $',
format(CI, '.2f'))
if st.checkbox("Show source code? "):
st.code(display.show_code("core/compound/CalcEngine.py"))
st.write(
"Forumla Source: https://www.thecalculatorsite.com/finance/calculators/compoundinterestcalculator.php"
)
def write():
#udisp.title_awesome("Summarized Text")
#st.title("Summarize Text")
summarytexteng.sum_main("Summarize Text", "Enter or paste text in the below box")
udisp.render_md("resources/summarytext2.md")
udisp.render_md("resources/summarytext.md")
# if st.checkbox("Show help document"):
# st.code(udisp.render_md("resources/summarytext.md"))
#udisp.render_md("resources/summarytext.md")
#st.write("@nagamayuri")
def write():
udisp.title_awesome("About")
udisp.render_md("resources/about.md")
def write():
#udisp.title_awesome("About")
udisp.render_md("resources/credits.md")
def write():
udisp.title_awesome('Sobre mim')
udisp.render_md("resources/about.md")
def write():
udisp.title_awesome("About")
udisp.render_md("resources/credits.md")
st.write("Thanks!!")
st.write("@avkashchauhan")
def run_main(title, subtitle):
st.write("Solve your Puzzle")
frameST = st.empty()
st.sidebar.title("Choose selection..")
if st.checkbox("Read Instructions before start? "):
udisp.render_md("resources/beforeyoustart.md")
puzzlesize_keys = globalDefine.PUZZLE_SIZE.keys()
puzzlesize_id = st.sidebar.selectbox("Select Puzzle Size: ",
list(puzzlesize_keys))
puzzle_size = globalDefine.PUZZLE_SIZE.get(puzzlesize_id)
model_list_keys = globalDefine.MODELS_LIST.keys()
model_master_id = st.sidebar.selectbox("Select Network type: ",
list(model_list_keys), 0)
model_master = globalDefine.MODELS_LIST.get(model_master_id)
input_img_type_keys = globalDefine.INPUT_TYPES.keys()
input_img_type_id = st.sidebar.selectbox("Select Image Location: ",
list(input_img_type_keys))
input_img_type = globalDefine.INPUT_TYPES.get(input_img_type_id)
problem_img_path = st.text_input(
'Please input puzzle image file/url here...')
solution_file_path = st.text_input(
'Please input target solution file/url here...')
progress_start = False
if st.checkbox("Validate input images and solve puzzle"):
st.write("Validating input path....")
if input_img_type == "LOCAL":
problem_valid = filemgmt.validateLocalPath(problem_img_path)
solution_valid = filemgmt.validateLocalPath(solution_file_path)
else:
##problem_valid = filemgmt.validateUrlPath(problem_img_path)
##if problem_valid:
problem_valid, problem_img_path = filemgmt.processPuzzleUrl(
problem_img_path)
##solution_valid = filemgmt.validateUrlPath(solution_file_path)
##if solution_valid:
solution_valid, solution_file_path = filemgmt.processSolutionUrl(
solution_file_path)
st.write(problem_img_path)
st.write(solution_file_path)
if (problem_valid and solution_valid):
st.write("Success: Both file contents are valid..")
progress_start = True
else:
st.write("Error: Both file contents are invalid..")
if progress_start:
##st.image(problem_img_path)
##st.image(solution_file_path)
## Step 1.1 - Original Input Image (Selected) >>> SOLUTION
input_img_url = ImageFormater.setup_image_requirements(
solution_file_path, puzzle_size)
original_image_np = np.array(Image.open(input_img_url).convert('RGB'))
st.image(original_image_np)
## Step 1.2 - Shuffled Image (Auto) >>>> PROBLEM
##shuffled_image_np, original_image_blocks, key_map_orig, blk_size, shuffle_img_blks = ImageScrambler.shuffle_image(problem_img_path, puzzle_size)
problem_img_url = ImageFormater.setup_image_requirements(
problem_img_path, puzzle_size)
shuffled_image_np = np.array(
Image.open(problem_img_url).convert('RGB'))
st.image(shuffled_image_np)
blk_size, shuffle_img_blks = ImageScrambler.zigsaw_image(
shuffled_image_np, puzzle_size)
st.title(" Start Solving Puzzle......")
## Using Shuffled Image
st.write("Generating Training Data...")
training_image_files = ImageToTrainAndTestData.generate_training_data(
shuffled_image_np, puzzle_size)
st.write("Total ", len(training_image_files),
" training image files are generated!!")
## TODO: Verify all the files on disk to make sure they do exist
## Using Original Image
st.write("Generating Test Data...")
test_image_files = ImageToTrainAndTestData.generate_test_data(
input_img_url, puzzle_size)
st.write("Total ", len(test_image_files),
" test image files are generated!!")
## TODO: Verify all the files on disk to make sure they do exist
st.write("Loading Training and Test Data for Deep Learning... ")
imgs_train = ImageToTrainAndTestData.load_images_into_memory(
training_image_files, "train_img", 'train')
imgs_test = ImageToTrainAndTestData.load_images_into_memory(
test_image_files, "test_img", 'test')
st.write("Total ", len(imgs_train), " training and ", len(imgs_test),
" test images are loaded into memory for deep learning")
st.title("Now starting deep learning using {} Network..".format(
model_master))
n_epochs = None
st.write("Preparing model configuration...")
shape_img = imgs_train[0].shape
model, shape_img_resize, input_shape_model, output_shape_model, n_epochs, outDir = ModelBuilder.config_model_builder(
model_master, shape_img)
st.write("Displaying model summary.. ")
if model_master in ["simpleAE", "convAE"]:
st.write(model.info)
elif model_master in ["vgg19"]:
st.write(model.summary())
st.write(
"Transforming training and test data based on selected model type.. "
)
X_train, X_test = ModelBuilder.applying_transformer(
shape_img_resize, imgs_train, imgs_test, input_shape_model)
st.write(
"First checking the stored model and if not found then building it.."
)
all_model_files = ModelBuilder.get_saved_models_info(outDir)
if (len(all_model_files)) == 0:
st.write(
"Start building model (The batch counts are {} for this process.)... Please wait..."
.format(n_epochs))
model = ModelBuilder.start_batch_process(model_master, X_train,
model, n_epochs)
else:
st.write(
"Model is already available so we are not building it to expedite the demo......"
)
st.write("Verifing model stored into disk..")
all_model_files = ModelBuilder.get_saved_models_info(outDir)
st.write(all_model_files)
st.write("Generate embeddings by using model.. ")
E_train_flatten, E_test_flatten = ModelBuilder.generate_embedding_from_model(
model, X_train, X_test, output_shape_model)
st.write("Fitting KNN Model..")
knn_neighbors = 5
knn_metric = "cosine"
knn = ModelBuilder.fit_knn_model(E_train_flatten, knn_neighbors,
knn_metric)
st.write(knn)
st.title("Generate final result map (image sequence)...")
final_list_map = ModelBuilder.generate_final_mapping_list(
knn, E_test_flatten)
st.write(final_list_map)
st.write(
"Reconstructing result image based on image sequence generate in previoud step... "
)
final_image_np = ModelBuilder.generate_final_result_image(
shuffled_image_np, blk_size, puzzle_size, shuffle_img_blks,
final_list_map)
st.image(final_image_np)
def write():
udisp.title_awesome("Puzzle Solver Home")
udisp.render_md("resources/home_info.md")
def write():
udisp.title_awesome("Step by Step Code Review")
udisp.render_md("resources/codestudy.md")
