Delete Textual Dataset Generation

Textual Dataset Generation/.idea/.gitignore

@@ -1,8 +0,0 @@
-# Default ignored files
-/shelf/
-/workspace.xml
-# Editor-based HTTP Client requests
-/httpRequests/
-# Datasource local storage ignored files
-/dataSources/
-/dataSources.local.xml

Textual Dataset Generation/.idea/Textual Dataset Generation.iml

@@ -1,9 +0,0 @@
-<?xml version="1.0" encoding="UTF-8"?>
-<module type="JAVA_MODULE" version="4">
-  <component name="NewModuleRootManager" inherit-compiler-output="true">
-    <exclude-output />
-    <content url="file://$MODULE_DIR$" />
-    <orderEntry type="inheritedJdk" />
-    <orderEntry type="sourceFolder" forTests="false" />
-  </component>
-</module>

Textual Dataset Generation/.idea/misc.xml

@@ -1,6 +0,0 @@
-<?xml version="1.0" encoding="UTF-8"?>
-<project version="4">
-  <component name="ProjectRootManager" version="2" languageLevel="JDK_11" default="true" project-jdk-name="11" project-jdk-type="JavaSDK">
-    <output url="file://$PROJECT_DIR$/out" />
-  </component>
-</project>

Textual Dataset Generation/.idea/modules.xml

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-<?xml version="1.0" encoding="UTF-8"?>
-<project version="4">
-  <component name="ProjectModuleManager">
-    <modules>
-      <module fileurl="file://$PROJECT_DIR$/.idea/Textual Dataset Generation.iml" filepath="$PROJECT_DIR$/.idea/Textual Dataset Generation.iml" />
-    </modules>
-  </component>
-</project>

Textual Dataset Generation/.idea/workspace.xml

@@ -1,83 +0,0 @@
-<?xml version="1.0" encoding="UTF-8"?>
-<project version="4">
-  <component name="ChangeListManager">
-    <list default="true" id="788fdcfa-b47d-4627-847f-ec90b9a0d9dd" name="Changes" comment="" />
-    <option name="SHOW_DIALOG" value="false" />
-    <option name="HIGHLIGHT_CONFLICTS" value="true" />
-    <option name="HIGHLIGHT_NON_ACTIVE_CHANGELIST" value="false" />
-    <option name="LAST_RESOLUTION" value="IGNORE" />
-  </component>
-  <component name="ProjectColorInfo"><![CDATA[{
-  "associatedIndex": 5
-}]]></component>
-  <component name="ProjectId" id="2hyRbehAgzDFNKMNHP7EtzBH3c2" />
-  <component name="ProjectViewState">
-    <option name="hideEmptyMiddlePackages" value="true" />
-    <option name="showLibraryContents" value="true" />
-  </component>
-  <component name="PropertiesComponent"><![CDATA[{
-  "keyToString": {
-    "Python.web scrap.executor": "Run",
-    "RunOnceActivity.OpenProjectViewOnStart": "true",
-    "RunOnceActivity.ShowReadmeOnStart": "true",
-    "kotlin-language-version-configured": "true",
-    "last_opened_file_path": "C:/Users/Amir/Desktop/Textual Dataset Generation",
-    "nodejs_package_manager_path": "npm",
-    "project.structure.last.edited": "SDKs",
-    "project.structure.proportion": "0.15",
-    "project.structure.side.proportion": "0.22758621",
-    "vue.rearranger.settings.migration": "true"
-  }
-}]]></component>
-  <component name="RunManager">
-    <configuration name="web scrap" type="PythonConfigurationType" factoryName="Python" nameIsGenerated="true">
-      <module name="Textual Dataset Generation" />
-      <option name="ENV_FILES" value="" />
-      <option name="INTERPRETER_OPTIONS" value="" />
-      <option name="PARENT_ENVS" value="true" />
-      <envs>
-        <env name="PYTHONUNBUFFERED" value="1" />
-      </envs>
-      <option name="SDK_HOME" value="" />
-      <option name="SDK_NAME" value="Python 3.11 (base)" />
-      <option name="WORKING_DIRECTORY" value="$PROJECT_DIR$" />
-      <option name="IS_MODULE_SDK" value="false" />
-      <option name="ADD_CONTENT_ROOTS" value="true" />
-      <option name="ADD_SOURCE_ROOTS" value="true" />
-      <EXTENSION ID="PythonCoverageRunConfigurationExtension" runner="coverage.py" />
-      <option name="SCRIPT_NAME" value="$PROJECT_DIR$/web scrap.py" />
-      <option name="PARAMETERS" value="" />
-      <option name="SHOW_COMMAND_LINE" value="false" />
-      <option name="EMULATE_TERMINAL" value="false" />
-      <option name="MODULE_MODE" value="false" />
-      <option name="REDIRECT_INPUT" value="false" />
-      <option name="INPUT_FILE" value="" />
-      <method v="2" />
-    </configuration>
-  </component>
-  <component name="SharedIndexes">
-    <attachedChunks>
-      <set>
-        <option value="jdk-11.0.21-corretto-11.0.21-3183f394aec4-d55de845" />
-      </set>
-    </attachedChunks>
-  </component>
-  <component name="SpellCheckerSettings" RuntimeDictionaries="0" Folders="0" CustomDictionaries="0" DefaultDictionary="application-level" UseSingleDictionary="true" transferred="true" />
-  <component name="TaskManager">
-    <task active="true" id="Default" summary="Default task">
-      <changelist id="788fdcfa-b47d-4627-847f-ec90b9a0d9dd" name="Changes" comment="" />
-      <created>1718564403600</created>
-      <option name="number" value="Default" />
-      <option name="presentableId" value="Default" />
-      <updated>1718564403600</updated>
-      <workItem from="1718564404645" duration="101000" />
-    </task>
-    <servers />
-  </component>
-  <component name="TypeScriptGeneratedFilesManager">
-    <option name="version" value="3" />
-  </component>
-  <component name="com.intellij.coverage.CoverageDataManagerImpl">
-    <SUITE FILE_PATH="coverage/Textual_Dataset_Generation$web_scrap.coverage" NAME="web scrap Coverage Results" MODIFIED="1718564477196" SOURCE_PROVIDER="com.intellij.coverage.DefaultCoverageFileProvider" RUNNER="coverage.py" COVERAGE_BY_TEST_ENABLED="true" COVERAGE_TRACING_ENABLED="false" WORKING_DIRECTORY="$PROJECT_DIR$" />
-  </component>
-</project>

Textual Dataset Generation/Dataset/input_dataset.csv

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-category,caption
-shoes,a person sitting on top of a wooden bench
-shoes,unpaired red Nike sneaker
-shoes,brown Nike sneaker on yellow textile
-shoes,unpaired maroon plimsoll on top of yellow textile
-shoes,a person with their feet up in the air
-shoes,white and blue nike air force 1 high
-shoes,pair of white-and-orange athletic shoes on white box
-shoes,green and black nike athletic shoe
-shoes,"Various colorful sports shoes laid on sand beach background, studio shot, flat lay."
-shoes,unpaired OFF WHITE X Nike Air Force 1 low-top sneaker
-shoes,white and red nike athletic shoe
-shoes,person wearing white Nike running shoes standing on black concrete path
-shoes,unpaired gray Nike running shoe
-shoes,pair of blue-and-pink floral almond-toe pumps
-shoes,pair of gray running shoes
-shoes,Close up of a young skater girl's feet and skateboard
-shoes,white black and red nike air max 90
-shoes,a pair of white and brown shoes on a table
-shoes,unpaired red Air Jordan 12
-sneakers,a man sitting on a brick wall next to a skateboard
-sneakers,a person wearing a hat
-sneakers,black white and red nike high top sneaker
-sneakers,two people sitting on the ground with their legs crossed
-sneakers,pair of black-white-and-red Air Jordan 1 shoes
-sneakers,Nike shoe lot
-sneakers,white nike air force 1 low
-sneakers,person wearing white nike sneakers
-sneakers,a man holding a pair of purple shoes
-sneakers,close-up photography of person wears brown-and-white Nike Air Max
-sneakers,person holding white and red heart print box
-sneakers,pair of Carhartt x Nike Air Force 1 shoes
-sneakers,Legs and sneakers of teenage boys and girls standing on the sidewalk
-sneakers,man sitting on the ledge of a building wearing Air Jordan 1 low-top shoes
-sneakers,blue white and red neon light
-sneakers,person wearing black pants and blue and white nike sneakers
-heels,a person standing on top of a wooden stool
-heels,woman in pink patent leather stilettos
-heels,woman in black leather heeled shoes
-heels,a pair of shoes sitting on top of a couch
-heels,red and white plastic frame on white table
-heels,pair of women's brown pointed-toe pumps on board
-heels,woman wearing brown leather heeled sandals walking on staircase
-heels,a pair of woman's legs wearing black gloves and red high heels
-heels,a pair of purple high heeled shoes on a woman's leg
-heels,person in black pants and red shoes
-heels,womens white and silver peep toe pumps
-heels,a woman wearing red high heels standing on a wooden floor
-heels,black leather boot on white surface
-heels,gray leather peep toe sandals
-heels,brown leather boots on white table
-heels,a woman's legs wearing red high heels
-heels,black leather peep toe heeled shoes
-heels,women's seven assorted-color footwear on surface
-heels,womens brown leather peep toe heeled shoes
-watches,a man is holding onto a railing in a room
-watches,blue and silver analog watch at 10 00
-watches,gold and white analog watch
-watches,round silver-colored analog watch with black strap
-watches,Close up of man putting watch on his hand.
-watches,brown and white analog watch at 10 10
-watches,round silver-colored watch on rack during sunset
-watches,silver and black chronograph watch
-watches,a person holding a cup of tea in their hand
-watches,round gray analog watch with brown band
-watches,watch at 10:34
-watches,silver and white round analog watch
-watches,Man in black suit wear new watches. Luxury style
-watches,person wearing silver link bracelet round analog watch
-watches,round silver-colored Nomos watch at 10:10
-watches,silver link bracelet round chronograph watch
-watches,a woman sitting at a table with a cell phone in her hand
-watches,black and silver round analog watch
-watches,watch at 8:45
-watches,blue and gold analog watch
-pants,three pairs of jeans are lined up on a white surface
-pants,person in pink pants and white shoes
-pants,blue denim jeans on white textile
-pants,person wears blue jeans
-pants,a pair of black leather boots sitting on top of a pile of blue jeans
-pants,man wearing brown fitted jeans and sneakers standing on road at daytime
-pants,three assorted-color denim bottoms
-pants,blue denim jeans on brown clothes hanger
-pants,a man walking across a bridge carrying a suitcase
-pants,man in white t-shirt and black pants standing on white floor
-pants,woman in orange pants
-pants,selective focus photography of hanged denim jeans
-pants,a person sitting on a bench with their legs crossed
-pants,woman in blue denim jeans and white sneakers
-pants,blue denim jeans on black surface
-pants,a pair of hands holding a pair of jeans
-pants,closeup photo of person hiding his right hand in his pocket
-pants,woman in white tank top and blue denim jeans standing on beach during daytime
-pants,woman in gray tank top and gray pants
-clothing,a piece of cloth sitting on top of a table
-clothing,"gray cardigan, blue jeans, and pair of brown chunky heeled shoes"
-clothing,green clothes hanger
-clothing,closeup of hanged shirts on rack
-clothing,a woman holding a pair of jeans
-clothing,women's white long sleeve shirt
-clothing,pair of white low-top sneakers
-clothing,hanged jeans lot
-clothing,a close up of a pair of blue jeans
-clothing,gray dress shirt hang on brown wooden rack in front of window with white curtain
-clothing,white and red nike air force 1 high
-clothing,woman standing selecting clothes
-clothing,a stack of folded clothes on a table next to a lamp
-clothing,woman waering black blouse and hat
-clothing,woman in red long sleeve dress
-clothing,assorted color folded shirts on wooden panel
-clothing,a pile of folded clothes sitting on top of a brown leather chair
-clothing,selective focus photography of hanged three gray tee shirts
-clothing,white and blue cat-printed crew-neck T-shirt
-clothing,assorted-color shirt lot hang on rack
-dress,a woman sitting on a bed in a room
-dress,woman in red sleeveless dress standing on gray concrete floor during daytime
-dress,green sleeveless dress hanged on white wall
-dress,woman in seashore
-dress,a woman standing on a beach holding a banana leaf
-dress,woman walking on seaside while holding woven bag
-dress,woman in yellow and white floral dress
-dress,woman wearing black turtleneck long-sleeved dress
-dress,a woman kneeling on a white background posing for a picture
-dress,woman walking down stair under clear blue sky during daytime
-dress,black leather spaghetti strap dress
-dress,woman standing in front of white wall
-dress,woman in beige floral sleeveless dress
-dress,woman wearing pink dress while standing near black metal rail at daytime
-dress,a rack of clothes hanging on a wall
-dress,woman in brown long sleeve dress standing beside gray wall
-dress,woman in green long sleeve dress standing on brown field during daytime
-dress,selective focus photo of smiling woman wearing black dress standing on concrete pavement
-shirt,a close up of an umbrella with a metal handle
-shirt,white crew neck t-shirt
-shirt,man in white dress shirt wearing black sunglasses
-shirt,gray button up long sleeve shirt
-shirt,"A young businessman standing in corridor outside office, looking at camera."
-shirt,black crew neck t-shirt
-shirt,blue and white checkered dress shirt
-shirt,man in black and white plaid button up shirt wearing black sunglasses
-shirt,white button up shirt on clothes hanger
-shirt,white crew neck long sleeve shirt
-shirt,A fathers day greeting card concept. Flat lay. Copy space.
-shirt,man in white dress shirt with black and white polka dots necktie
-shirt,woman wearing orange crew-neck sweatshirt standing while putting right hand on her head
-shirt,a person holding a white shirt on a hanger
-shirt,man in blue dress shirt wearing black sunglasses
-shirt,man in white crew neck t-shirt standing on green grass field during daytime
-t-shirt,a young man wearing a black shirt and a chain around his neck
-t-shirt,man wearing white crew-neck t-shirts
-t-shirt,a woman sitting on the floor with her legs crossed
-t-shirt,man in white crew neck t-shirt
-t-shirt,smiling woman in black and white print t-shirt
-t-shirt,woman in black crew neck t-shirt and blue denim jeans
-t-shirt,photo of blue crew-neck tops
-t-shirt,a woman in a white shirt and a pink hat
-t-shirt,woman in black crew neck t-shirt standing near painting
-t-shirt,men's white crew-neck t-shirt
-t-shirt,man wearing white crew-neck t-shirt
-t-shirt,man in pink crew neck t-shirt wearing black sunglasses
-t-shirt,man in black crew neck t-shirt standing during daytime

Textual Dataset Generation/main.py

@@ -1,256 +0,0 @@
-import json
-import pandas as pd
-
-color_changes = [
-    ("black", "Change * color to black"),
-    ("white", "Change * color to white"),
-    ("red", "Change * color to red"),
-    ("blue", "Change * color to blue"),
-    ("orange", "Change * color to orange"),
-    ("purple", "Change * color to purple"),
-]
-
-scene_changes = [
-    ("by the beach", "put * by the beach"),
-    ("in the desert", "put * in the desert"),
-    ("* in a festival", "put it in a festival"),
-    ("on a table", "put * on a table"),
-    ("in a forest", "put * in a forest"),
-    ("on a roof", "put * on a roof"),
-    ("in the air", "make * in the air"),
-    ("in hands", "put * in someone`s hands"),
-    ("covered with water", "put * in water"),
-]
-
-season_changes = [
-    ("in snow", "add snow effects"),
-    ("in spring", "add spring effects"),
-    ("in summer", "add summer effects"),
-    ("in autumn", "add autumn effects"),
-    ("during daytime", "make the scene in daytime"),
-    ("during nighttime", "make the period in nighttime"),
-]
-
-background_changes = [
-    ("in front of a mountain", "add mountain in the background"),
-    ("in front of the pyramids", "add the pyramids in the background"),
-]
-
-PRODUCTS = [
-    "t-shirt",
-    "shirt",
-    "dress",
-    "pants",
-    "shoe",
-    "watch",
-    "vase",
-    "sneaker",
-    "headphone",
-    "bottle",
-    "perfume",
-    "vase",
-    "cup",
-    "camera",
-    "phone",
-    "mobile",
-    "bag",
-    "earpod",
-    "earbud",
-    "heel",
-]
-
-
-def find_words(lst, input):
-    found_words = []
-    for w in lst:
-        indx = input.find(w)
-        if indx != -1:
-            if indx + len(w) + 1 < len(input) and input[indx + len(w) + 1] == "s":
-                w += "s"
-
-            found_words.append(w)
-
-    return found_words
-
-
-def perform_color_changes(input, mixed_color=False):
-    if input.endswith("s"):
-        input = input[:-1]
-
-    original_input = input
-    result = []
-    found_words = find_words(PRODUCTS, input)
-
-    # remove colors to avoid repeated consecutive colors
-    for change, _ in color_changes:
-        changee = " "
-        if mixed_color == True:
-            changee = change + "-"
-
-        input = input.replace(str(" " + change + " "), changee).replace("  ", " ")
-
-    for word in found_words:
-        for change, change_text in color_changes:
-            edit = change_text.replace("*", word)
-            changed = str(change + " " + word)
-            output = input.replace(word, changed)
-
-            result.append({"caption": original_input, "edit": edit, "output": output})
-
-    return result
-
-
-def perform_scene_changes(input):
-    original_input = input
-    for change, _ in scene_changes:
-        input = input.replace(change, "")
-
-    result = []
-    found_words = find_words(PRODUCTS, input)
-    for word in found_words:
-        for change, change_text in scene_changes:
-            edit = change_text
-            edit = edit.replace("*", word)
-
-            output = input + " " + change
-
-            result.append(
-                {
-                    "caption": original_input,
-                    "edit": edit,
-                    "output": output.replace("  ", " "),
-                }
-            )
-
-    return result
-
-
-def perform_affects_changes(input):
-    original_input = input
-    for change, _ in background_changes:
-        input = input.replace(change, "")
-
-    result = []
-    found_words = find_words(PRODUCTS, input)
-
-    for _ in found_words:
-        for change, change_text in season_changes:
-            edit = change_text
-            output = input + " " + change
-
-            result.append(
-                {
-                    "caption": original_input,
-                    "edit": edit,
-                    "output": output.replace("  ", " "),
-                }
-            )
-
-        break
-    return result
-
-
-def perform_background_changes(input):
-    original_input = input
-    for change, _ in background_changes:
-        input = input.replace(change, "")
-
-    result = []
-    found_words = find_words(PRODUCTS, input)
-
-    for _ in found_words:
-        for change, change_text in background_changes:
-            edit = change_text
-            output = input + " " + change
-
-            result.append(
-                {
-                    "caption": original_input,
-                    "edit": edit,
-                    "output": output.replace("  ", " "),
-                }
-            )
-        break
-
-    return result
-
-
-def get_rows(input):  # return: list of dictionary
-    input = input.lower().replace("-", " ")
-    # remove brands
-    input = input.replace("nike ", "")
-    result = []
-
-    color_changes_result = perform_color_changes(input, False)
-    for new_row in color_changes_result:
-        result.append(new_row)
-
-    scene_changes_result = perform_scene_changes(input)
-    for new_row in scene_changes_result:
-        result.append(new_row)
-
-    affects_changes_result = perform_affects_changes(input)
-    for new_row in affects_changes_result:
-        result.append(new_row)
-
-    background_changes_result = perform_background_changes(input)
-    for new_row in background_changes_result:
-        result.append(new_row)
-
-    return result
-
-
-def statistics(strs):
-    total = 0
-    stat = {}
-    for product in PRODUCTS:
-        cntr = sum(product.lower() in s.lower() for s in strs)
-        total += cntr
-        stat[product] = cntr
-
-    stat = dict(sorted(stat.items(), key=lambda item: item[1], reverse=True))
-
-    return stat, total
-
-
-def load_dataset(path):
-
-    dataset = pd.read_csv(path)
-    return dataset
-
-
-def save_dataset(data, file_path):
-    with open(file_path, "w") as file:
-        for idx in range(len(data)):
-            json_string = json.dumps(data[idx]) + ("\n" if idx < len(data) - 1 else "")
-            file.write(json_string)
-
-
-def insert_row(df, new_data: list):
-    # Create a DataFrame with the new row data
-    new_data = pd.DataFrame(new_data, columns=df.columns)
-    # Append the new row to the existing DataFrame
-    df = df.append(new_data, ignore_index=True)
-    return df
-
-
-def main():
-    input_dataset = load_dataset("Dataset/input_dataset.csv")
-    outout_dataset = []
-
-    for val in input_dataset["caption"]:
-        newData = get_rows(val)
-        if len(newData) > 0:
-            outout_dataset += newData
-
-    stat, total = statistics([item["caption"] for item in outout_dataset])
-    stat = pd.DataFrame([stat]).transpose()
-
-    print(rf"TOTAL : {total}")
-    print(stat)
-
-    save_dataset(outout_dataset, "Dataset/textual_dataset.jsonl")
-
-
-if __name__ == "__main__":
-    main()

Textual Dataset Generation/web scrap.py

@@ -1,66 +0,0 @@
-import pandas as pd
-import requests
-from bs4 import BeautifulSoup
-import time
-
-
-def scrap(url: str):
-    try:
-        response = requests.get(url)
-        response.raise_for_status()  # Raise an error for bad status codes
-    except requests.exceptions.RequestException as e:
-        print(f"Error fetching {url}: {e}")
-        return None
-
-    # Parse the HTML content
-    soup = BeautifulSoup(response.content, "html.parser")
-
-    div_elements = soup.find_all("div", class_="WxXog")
-    result = []
-    for div in div_elements:
-        img_tag = div.find("img")
-        if img_tag:
-            alt_text = img_tag.get("alt")
-            if alt_text is not None and len(alt_text) < 100:
-                result.append(alt_text)
-
-    return result
-
-
-def main():
-    data = []
-
-    categories = [
-        "shoes",
-        "sneakers",
-        "heels",
-        "watches",
-        "pants",
-        "clothing",
-        "dress",
-        "shirt",
-        "t-shirt",
-    ]
-    seen_inputs = set()
-    base_url = "https://unsplash.com/s/photos/"
-
-    for category in categories:
-        url = f"{base_url}{category}"
-        print(f"Scraping {url}...")
-        res = scrap(url)
-        if res is not None:
-            for t in res:
-                if t not in seen_inputs:
-                    data.append({"category": category, "caption": t})
-                    seen_inputs.add(t)
-
-        time.sleep(1)  # Delay to avoid rate limiting
-
-    df = pd.DataFrame(data)
-
-    # Save to CSV
-    df.to_csv("input_dataset.csv", index=False)
-
-
-if __name__ == "__main__":
-    main()