Haiku-ASCII-art-examples.ipynb

{"cells":[{"attachments":{},"cell_type":"markdown","id":"192680e4-9009-4bb2-8053-2b8e81517eff","metadata":{"language":"python"},"source":"## Generating and Visualizing a Haiku"},{"attachments":{},"cell_type":"markdown","id":"d0c6cc06-e413-4154-b3d1-c7dec9239bc3","metadata":{"language":"python"},"source":"Come up with a HAIKU or ASCII art using SingleStore Notebooks. Below are some examples on creating Haiku for your reference."},{"attachments":{},"cell_type":"markdown","id":"54676c95-d210-42d3-9dab-2a660b0fd901","metadata":{"language":"python"},"source":"This below code consists of two main parts:\n\n1. Generating a Haiku: The generate_haiku function creates a simple haiku using pre-defined lists of phrases that correspond to the traditional 5-7-5 syllable structure of haikus. This function randomly selects one phrase from each list to construct the haiku.\n\n2. Visualizing the Haiku: The visualize_haiku function uses matplotlib to create a visualization of the generated haiku. It sets up a figure with a custom background color, hides the axes for a cleaner look, and displays the haiku text in the center with a styled bounding box around it."},{"cell_type":"code","execution_count":17,"id":"a30655d6-9180-467c-aab9-0fc70ce50812","metadata":{"execution":{"iopub.execute_input":"2024-04-02T05:08:47.922826Z","iopub.status.busy":"2024-04-02T05:08:47.922570Z","iopub.status.idle":"2024-04-02T05:08:52.813031Z","shell.execute_reply":"2024-04-02T05:08:52.812387Z","shell.execute_reply.started":"2024-04-02T05:08:47.922810Z"},"language":"python","trusted":true},"outputs":[],"source":"!pip install matplotlib --quiet"},{"attachments":{},"cell_type":"markdown","id":"986a1bd7-65f1-43e5-b135-9f63dc89cb3c","metadata":{"language":"python"},"source":"### Example 1"},{"cell_type":"code","execution_count":19,"id":"6a701c9e-d814-4874-ab7e-5a3d84996ef6","metadata":{"execution":{"iopub.execute_input":"2024-04-02T05:08:57.866955Z","iopub.status.busy":"2024-04-02T05:08:57.866690Z","iopub.status.idle":"2024-04-02T05:08:58.408401Z","shell.execute_reply":"2024-04-02T05:08:58.407857Z","shell.execute_reply.started":"2024-04-02T05:08:57.866938Z"},"language":"python","trusted":true},"outputs":[{"data":{"image/png":"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","text/plain":"<Figure size 800x600 with 1 Axes>"},"metadata":{},"output_type":"display_data"}],"source":"import matplotlib.pyplot as plt\nimport numpy as np\n\n# Simple Haiku Generator Function\ndef generate_haiku():\n    # Example words for simplicity, replace or expand as needed\n    five_syllables = [\"The silent sunset\", \"Mountains in the fall\", \"Waves crash on the shore\"]\n    seven_syllables = [\"Clouds cover the moon tonight\", \"A quiet pond reflects stars\", \"Leaves rustle in the wind's song\"]\n    \n    # Randomly select lines to form a haiku\n    haiku = [\n        np.random.choice(five_syllables),\n        np.random.choice(seven_syllables),\n        np.random.choice(five_syllables)\n    ]\n    return haiku\n\n# Advanced Visualization Function with matplotlib\ndef visualize_haiku(haiku):\n    # Create a figure and axis for drawing\n    fig, ax = plt.subplots(figsize=(8, 6))\n    \n    # Hide axes\n    ax.axis('off')\n    \n    # Set background (using an example pattern or image)\n    # For a more advanced approach, you could dynamically load an image that matches the theme of the haiku\n    bg_color = '#f0eade'  # Example: a paper-like background color\n    fig.patch.set_facecolor(bg_color)\n    ax.set_facecolor(bg_color)\n    \n    # Display the haiku text\n    haiku_text = \"\\n\".join(haiku)\n    bbox_props = dict(boxstyle=\"round,pad=0.3\", ec=\"black\", lw=2, facecolor=\"white\")\n    ax.text(0.5, 0.5, haiku_text, fontsize=20, va='center', ha='center', bbox=bbox_props)\n    \n    plt.show()\n\n# Generate and Visualize Haiku\nhaiku = generate_haiku()\nvisualize_haiku(haiku)"},{"attachments":{},"cell_type":"markdown","id":"ad95e2d1-6b4e-4981-8487-d368adecc19e","metadata":{"language":"python"},"source":"Something similar below"},{"attachments":{},"cell_type":"markdown","id":"fd315e29-c629-4d86-9c3f-275133490169","metadata":{"language":"python"},"source":"### Example 2"},{"cell_type":"code","execution_count":44,"id":"714274a7-0c7c-4b9b-959c-5a4d2ea41cf3","metadata":{"execution":{"iopub.execute_input":"2024-04-02T05:12:47.722723Z","iopub.status.busy":"2024-04-02T05:12:47.722296Z","iopub.status.idle":"2024-04-02T05:12:47.864121Z","shell.execute_reply":"2024-04-02T05:12:47.863599Z","shell.execute_reply.started":"2024-04-02T05:12:47.722704Z"},"language":"python","trusted":true},"outputs":[{"name":"stdout","output_type":"stream","text":"Background image sunset.jpg not found. Using plain background.\n"},{"data":{"image/png":"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","text/plain":"<Figure size 1000x800 with 1 Axes>"},"metadata":{},"output_type":"display_data"}],"source":"import matplotlib.pyplot as plt\nimport numpy as np\nfrom matplotlib.offsetbox import OffsetImage, AnnotationBbox\nfrom PIL import Image\nimport os\n\n# Expanded Haiku Generator Function\ndef generate_haiku():\n    five_syllables = [\"The silent sunset\", \"Mountains in the fall\", \"Waves crash on the shore\",\n                      \"Early morning dew\", \"Whispers of the night\"]\n    seven_syllables = [\"Clouds cover the moon tonight\", \"A quiet pond reflects stars\",\n                       \"Leaves rustle in the wind's song\", \"Footprints vanish in the snow\",\n                       \"The city sleeps under stars\"]\n    \n    haiku = [\n        np.random.choice(five_syllables),\n        np.random.choice(seven_syllables),\n        np.random.choice(five_syllables)\n    ]\n    return haiku\n\n# Advanced Visualization Function with Dynamic Background\ndef visualize_haiku(haiku):\n    fig, ax = plt.subplots(figsize=(10, 8))\n\n    ax.axis('off')\n\n    # Example backgrounds\n    backgrounds = {\n        \"The silent sunset\": \"sunset.jpg\",\n        \"Mountains in the fall\": \"mountains.jpg\",\n        \"Waves crash on the shore\": \"waves.jpg\",\n        # Add paths for new images here\n    }\n    \n    haiku_theme = haiku[0]  # Use the first line to determine the theme\n    bg_image_path = backgrounds.get(haiku_theme, \"default_background.jpg\")  # Fallback to a default image\n    \n    try:\n        img = Image.open(bg_image_path)\n        img = img.resize((fig.bbox.xmax, fig.bbox.ymax), Image.ANTIALIAS)\n        ax.imshow(img, extent=[0, 1, 0, 1], aspect='auto')\n    except FileNotFoundError:\n        print(f\"Background image {bg_image_path} not found. Using plain background.\")\n        bg_color = '#f0eade'\n        fig.patch.set_facecolor(bg_color)\n        ax.set_facecolor(bg_color)\n\n    haiku_text = \"\\n\".join(haiku)\n    bbox_props = dict(boxstyle=\"round,pad=0.3\", ec=\"black\", lw=2, facecolor=\"white\", alpha=0.7)\n    ax.text(0.5, 0.5, haiku_text, fontsize=20, va='center', ha='center', bbox=bbox_props, wrap=True)\n    \n    plt.title(\"A Haiku for You\", fontsize=24, weight='bold', color='black')\n    \n    plt.show()\n\n# Generate and Visualize Haiku\nhaiku = generate_haiku()\nvisualize_haiku(haiku)"},{"attachments":{},"cell_type":"markdown","id":"b6c7e5c0-fb70-47bb-9f87-8f4770dd26ac","metadata":{"language":"python"},"source":"### Example 3"},{"cell_type":"code","execution_count":76,"id":"1f236018-5a2f-4cf8-a98a-dd21e6552ca0","metadata":{"execution":{"iopub.execute_input":"2024-04-02T05:19:15.686263Z","iopub.status.busy":"2024-04-02T05:19:15.685436Z","iopub.status.idle":"2024-04-02T05:19:15.750191Z","shell.execute_reply":"2024-04-02T05:19:15.749557Z","shell.execute_reply.started":"2024-04-02T05:19:15.686241Z"},"language":"python","trusted":true},"outputs":[{"data":{"image/png":"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","text/plain":"<Figure size 1000x600 with 1 Axes>"},"metadata":{},"output_type":"display_data"}],"source":"import matplotlib.pyplot as plt\nimport numpy as np\nimport matplotlib.patches as patches\n\n# Haiku Generator with Environmental Themes\ndef generate_environmental_haiku():\n    lines = {\n        \"start\": [\"Dawn's light on leaves\", \"Moonlit whispering pines\", \"Sunset's final glow\"],\n        \"middle\": [\"Rivers carve the earth\", \"Mountains touch the sky's edge\", \"Forests breathe with life\"],\n        \"end\": [\"Night's curtain falls\", \"Autumn's crisp exhale\", \"Spring's chorus awakens\"]\n    }\n    \n    haiku = [\n        np.random.choice(lines[\"start\"]),\n        np.random.choice(lines[\"middle\"]),\n        np.random.choice(lines[\"end\"])\n    ]\n    return haiku\n\n# Dynamic Visualization Function\ndef visualize_dynamic_haiku(haiku):\n    fig, ax = plt.subplots(figsize=(10, 6))\n    ax.set_xlim(0, 10)\n    ax.set_ylim(0, 10)\n    ax.axis('off')\n    \n    # Background Color\n    ax.set_facecolor(\"#e0f7fa\")\n    \n    # Dynamic elements based on the Haiku\n    if \"Dawn's light\" in haiku[0]:\n        ax.add_patch(patches.Circle((5, 5), 3, color=\"#fdd835\"))  # Sun\n    elif \"Moonlit\" in haiku[0]:\n        ax.add_patch(patches.Circle((5, 5), 3, color=\"#cfd8dc\"))  # Moon\n    elif \"Sunset's\" in haiku[0]:\n        ax.add_patch(patches.Circle((5, 5), 3, color=\"#ef5350\"))  # Setting Sun\n    \n    if \"Rivers\" in haiku[1]:\n        ax.plot([2, 8], [2, 2], color=\"#29b6f6\", linewidth=5)  # River\n    elif \"Mountains\" in haiku[1]:\n        ax.add_patch(patches.Polygon([[3,3], [5,7], [7,3]], closed=True, color=\"#8d6e63\"))  # Mountain\n    elif \"Forests\" in haiku[1]:\n        ax.add_patch(patches.Rectangle((3, 2), 4, 4, color=\"#66bb6a\"))  # Forest\n    \n    # Haiku Text\n    ax.text(5, 1, \"\\n\".join(haiku), ha='center', fontsize=12, style='italic', bbox=dict(facecolor='white', alpha=0.5))\n    \n    plt.show()\n\n# Generate and Visualize Haiku\nhaiku = generate_environmental_haiku()\nvisualize_dynamic_haiku(haiku)"},{"attachments":{},"cell_type":"markdown","id":"08d1b7fb-bf75-4157-a615-3e798708cb85","metadata":{"language":"python"},"source":"### Example 4"},{"cell_type":"code","execution_count":101,"id":"5f4d1299-17c2-47ae-9875-1870320f6e8c","metadata":{"execution":{"iopub.execute_input":"2024-04-02T05:23:38.383927Z","iopub.status.busy":"2024-04-02T05:23:38.383622Z","iopub.status.idle":"2024-04-02T05:23:38.462183Z","shell.execute_reply":"2024-04-02T05:23:38.461695Z","shell.execute_reply.started":"2024-04-02T05:23:38.383907Z"},"language":"python","trusted":true},"outputs":[{"data":{"image/png":"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size 1000x600 with 1 Axes>"},"metadata":{},"output_type":"display_data"}],"source":"import numpy as np\nimport matplotlib.pyplot as plt\nfrom matplotlib.colors import LinearSegmentedColormap\n\n# Seasonal Transition Haiku Generator\ndef generate_seasonal_transition_haiku():\n    seasons = [\"Winter\", \"Spring\", \"Summer\", \"Fall\"]\n    transitions = {\n        (\"Winter\", \"Spring\"): [\"Snow melts, streams flow\", \"Green buds break through frost\", \"Life awakens anew\"],\n        (\"Spring\", \"Summer\"): [\"Flowers bloom in warmth\", \"Longer days, brighter sun\", \"Nature in full swing\"],\n        (\"Summer\", \"Fall\"): [\"Leaves turn gold and red\", \"Harvest moon rises high\", \"Chill whispers in the wind\"],\n        (\"Fall\", \"Winter\"): [\"First frost coats the ground\", \"Days shorten, nights grow long\", \"Silence under the snow\"],\n    }\n    \n    # Randomly select a transition\n    start_season = np.random.choice(seasons)\n    end_season = seasons[(seasons.index(start_season) + 1) % len(seasons)]\n    \n    haiku_lines = transitions[(start_season, end_season)]\n    \n    return haiku_lines, start_season, end_season\n\n# Visualization with Gradient\ndef visualize_seasonal_transition(haiku, start_season, end_season):\n    fig, ax = plt.subplots(figsize=(10, 6))\n    ax.axis('off')\n    \n    # Seasonal Colors\n    colors = {\n        \"Winter\": \"#ffffff\",\n        \"Spring\": \"#4caf50\",\n        \"Summer\": \"#ffa726\",\n        \"Fall\": \"#fb8c00\"\n    }\n    \n    # Create Gradient\n    cmap = LinearSegmentedColormap.from_list(\"season_transition\", [colors[start_season], colors[end_season]])\n    gradient = np.linspace(0, 1, 256)\n    gradient = np.vstack((gradient, gradient))\n    \n    ax.imshow(gradient, aspect='auto', cmap=cmap, extent=[0, 10, 0, 10])\n    \n    # Display Haiku\n    ax.text(5, 5, \"\\n\".join(haiku), ha='center', va='center', fontsize=14, color=\"black\")\n    \n    plt.show()\n\n# Generate and Visualize\nhaiku, start_season, end_season = generate_seasonal_transition_haiku()\nvisualize_seasonal_transition(haiku, start_season, end_season)"},{"attachments":{},"cell_type":"markdown","id":"cdbf93dc-0a23-4fd7-8e05-b3be6eadeea2","metadata":{"language":"python"},"source":"### Example 5"},{"cell_type":"code","execution_count":124,"id":"0c6e1cf7-2b5c-4f68-8181-96cb1db4e30e","metadata":{"execution":{"iopub.execute_input":"2024-04-02T05:27:10.288130Z","iopub.status.busy":"2024-04-02T05:27:10.287859Z","iopub.status.idle":"2024-04-02T05:27:10.355894Z","shell.execute_reply":"2024-04-02T05:27:10.355401Z","shell.execute_reply.started":"2024-04-02T05:27:10.288110Z"},"language":"python","trusted":true},"outputs":[{"data":{"image/png":"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","text/plain":"<Figure size 800x800 with 1 Axes>"},"metadata":{},"output_type":"display_data"}],"source":"import numpy as np\nimport matplotlib.pyplot as plt\nimport matplotlib.patches as patches\n\n# Day and Night Haiku Generator\ndef generate_day_night_haiku():\n    day_lines = [\"Sunrise ignites skies\", \"Noon's bright, unyielding gaze\", \"Sunset's soft goodbye\"]\n    night_lines = [\"Moon's gentle glow\", \"Stars whisper ancient tales\", \"Night's deep, serene veil\"]\n    \n    # Creating a Haiku that represents a cycle from day to night and back\n    haiku = [np.random.choice(day_lines), np.random.choice(night_lines), np.random.choice(day_lines)]\n    return haiku\n\n# Circular Visualization for Day and Night Cycle\ndef visualize_day_night_cycle(haiku):\n    fig, ax = plt.subplots(figsize=(8, 8), subplot_kw={'aspect': 'equal'})\n    ax.axis('off')\n    \n    # Drawing the Sun and Moon\n    sun = patches.Circle((0.3, 0.75), 0.2, color=\"#FFD54F\", transform=ax.transAxes)  # Sun\n    moon = patches.Circle((0.7, 0.25), 0.15, color=\"#CFD8DC\", transform=ax.transAxes)  # Moon\n    \n    ax.add_patch(sun)\n    ax.add_patch(moon)\n    \n    # Drawing the path representing the cycle\n    cycle_path = patches.Arc((0.5, 0.5), 0.8, 0.8, angle=0, theta1=0, theta2=360, edgecolor='gray', transform=ax.transAxes)\n    ax.add_patch(cycle_path)\n    \n    # Displaying the Haiku text in the center\n    ax.text(0.5, 0.5, \"\\n\".join(haiku), ha='center', va='center', fontsize=14, color=\"black\")\n\n    plt.show()\n\n# Generate and Visualize the Day and Night Cycle Haiku\nhaiku = generate_day_night_haiku()\nvisualize_day_night_cycle(haiku)"},{"attachments":{},"cell_type":"markdown","id":"d054194b-8acd-44ac-a0ae-bfaa3c80e9a9","metadata":{"language":"python"},"source":"### Example 6"},{"cell_type":"code","execution_count":230,"id":"7958d112-7a62-4b32-8c5a-3f1eb60ddf69","metadata":{"execution":{"iopub.execute_input":"2024-04-02T05:44:45.593566Z","iopub.status.busy":"2024-04-02T05:44:45.593301Z","iopub.status.idle":"2024-04-02T05:44:45.830395Z","shell.execute_reply":"2024-04-02T05:44:45.829835Z","shell.execute_reply.started":"2024-04-02T05:44:45.593548Z"},"language":"python","trusted":true},"outputs":[{"data":{"image/png":"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","text/plain":"<Figure size 1000x600 with 1 Axes>"},"metadata":{},"output_type":"display_data"}],"source":"import matplotlib.pyplot as plt\nimport numpy as np\nfrom matplotlib.patches import Ellipse, Polygon\nfrom matplotlib.colors import LinearSegmentedColormap\n\n# Enhanced Haiku Function\ndef generate_abstract_haiku():\n    times_of_day = [\"Morning\", \"Noon\", \"Evening\", \"Night\"]\n    elements = [\"River\", \"Mountain\", \"Tree\", \"Stars\"]\n    moods = [\"Serene\", \"Vibrant\", \"Mysterious\", \"Peaceful\"]\n    \n    haiku = [\n        f\"{np.random.choice(times_of_day)}'s {np.random.choice(moods)} Light\",\n        f\"{np.random.choice(elements)} in the {np.random.choice(moods)}\",\n        f\"Echoes of {np.random.choice(elements)}\"\n    ]\n    return haiku\n\n# Visualization with Improved Text Integration\ndef visualize_abstract_landscape(haiku):\n    fig, ax = plt.subplots(figsize=(10, 6))\n    ax.axis('off')\n    \n    # Determine the sky's gradient based on the time of day in the Haiku\n    sky_colors = {\n        \"Morning\": [\"#FFDAB9\", \"#00BFFF\"],\n        \"Noon\": [\"#87CEEB\", \"#00BFFF\"],\n        \"Evening\": [\"#FFA07A\", \"#20B2AA\"],\n        \"Night\": [\"#2F4F4F\", \"#000000\"]\n    }\n    time_of_day = haiku[0].split(\"'\")[0]\n    sky_color = sky_colors.get(time_of_day, [\"#87CEEB\", \"#00BFFF\"])\n    ax.imshow(np.linspace(0, 1, 256).reshape(-1, 1), aspect='auto', extent=[0, 10, 0, 10], cmap=LinearSegmentedColormap.from_list(\"sky\", sky_color))\n    \n    # Simplified Examples of Environmental Elements\n    if \"River\" in haiku[1]:\n        river = Ellipse((5, 2), 9, 1, color=\"#1E90FF\", alpha=0.7)\n        ax.add_patch(river)\n    if \"Mountain\" in haiku[1]:\n        mountain = Polygon([[3,3], [5,7], [7,3]], closed=True, color=\"#A52A2A\", alpha=0.7)\n        ax.add_patch(mountain)\n    if \"Tree\" in haiku[1]:\n        tree = Ellipse((5, 5), 3, 6, color=\"#228B22\", alpha=0.7)\n        ax.add_patch(tree)\n    if \"Stars\" in haiku[2]:\n        for _ in range(50):\n            x, y = np.random.rand(2) * 10\n            star = Ellipse((x, y), 0.1, 0.1, color=\"#FFFFFF\", alpha=0.8)\n            ax.add_patch(star)\n    \n    # Improved Haiku Display in the Sky\n    text_y_position = 9  # Positioning the text higher in the visualization\n    for line in haiku:\n        ax.text(5, text_y_position, line, ha='center', va='center', fontsize=12, color=\"white\")\n        text_y_position -= 1  # Moving each line down\n\n    plt.show()\n\n# Generate an abstract Haiku\nhaiku = generate_abstract_haiku()\n\n# Visualize the Haiku with an enhanced abstract landscape\nvisualize_abstract_landscape(haiku)"},{"cell_type":"markdown","id":"0da8f807-9174-4493-a532-3e5166b092f2","metadata":{"language":"python"},"source":"## ASCII Art Generation"},{"cell_type":"code","execution_count":188,"id":"48335134-f5d9-42d9-bc98-68ba0e97f47d","metadata":{"execution":{"iopub.execute_input":"2024-04-03T15:37:06.526632Z","iopub.status.busy":"2024-04-03T15:37:06.526275Z","iopub.status.idle":"2024-04-03T15:37:08.080797Z","shell.execute_reply":"2024-04-03T15:37:08.080087Z","shell.execute_reply.started":"2024-04-03T15:37:06.526615Z"},"language":"python","trusted":true},"outputs":[],"source":"!pip install Pillow requests --quiet"},{"cell_type":"code","execution_count":214,"id":"9f3a0969-7aa9-4807-94cd-a915d327a258","metadata":{"execution":{"iopub.execute_input":"2024-04-03T15:40:57.962707Z","iopub.status.busy":"2024-04-03T15:40:57.962439Z","iopub.status.idle":"2024-04-03T15:41:05.214805Z","shell.execute_reply":"2024-04-03T15:41:05.214278Z","shell.execute_reply.started":"2024-04-03T15:40:57.962686Z"},"language":"python","trusted":true},"outputs":[{"name":"stdout","output_type":"stream","text":"%SSSSSSSS%%%%%%%SSSS%%%%%%%%%%%SSSS?*++;;;;;;;;;;+++?%%%%%SSSSSS%%%%%%%%%%%SS%%%%%S%%SSSSSSSSSSSSSSS\nSSSSSSSS%%SS%SS%SSS%%S%%%SS%%%SSS?*;;;;;;;;:;:;;;;;;+**?%%%SSSSSS%%%%%%%%%%%%%%%%%%S%SSSSSSSSSSSSSSS\nSSSSSS%S%%%%%S%%SSS%%SSSSS%%%SS%*+;;;:::::::::::::;;;;++?%%%%SSS#S%%%%%%%%%%%%%%%%SS%%SS%SSSSSSSSSSS\nSSSSS%%%%%%%%%%%%S%%S%SSS%%%SS%*+;:::::::::::::::::;;;;+*?%%%SSSS#S%%%%%%%%%%%%%%%%SSSSSSSSSSSSSSSS%\nSSSS%%%%%%%%%%%%%%%%%%%SS%%%SS*;;;::::::::::::::::::;;;++*?SSSSSS##S%%%%%%%%%%%%%%%%SSSSSSSSSSSSSSSS\nSSSS%%%%%S%%%%%%%%%%%%%%%SSSS?+;;:::::::::::::::::::;;;+++?%SSSSSSS#S%%%%%%%%%%%%%%%%SSSSSSSSSSSSSSS\nSSSSS%%%%S%%%%%%%S%%%%%%SSS#S*+;;:::::::::::::::::::;;;+++?SSSSSSSS##SS%%%%%%%%%%%%%%%SSSSSSSSSSSSSS\nSSSS%%S%%%%%%%%%SSSS%%%%SS##%*;;;::::::::::::::::::;;;++++*%SSS##S#####S%%%%%%%%%%%%%%%%SSS%%%SSSSSS\nSS%S%%S%S%%%%%%%S%%%%SSSS##S?++;;:::::::::::::::::;;;;++++*?SSSS##SS###SSS%%%%%%%%%%%%%%%SSSSSSS%SSS\nS%%%%%%%%%%%%%%%%%%SSSSSS##S?++;;;;;;;;::::::::::;;;;;+++**?%S%####SSS####SS%%%%%%%%%%%%%SS%SSSSSSS%\n%%%%%%%%%%%%%%%%%%%SS%%SSSSS*++;;;;;;;;;;;;;;;;;;;;;;+++++*?%%%S#SS###SSSS#SSS%%%%%%%%%%%%SSS%SSSSS%\n%%%%%%%%%%%%%%%%%%%S%%%%%S#%****?*+;;;;+++**????***++++++**??SSS##SSSS#SSS#SSSS%%%%%%%%%%%%SSSSSSSSS\n%%SS%%%%%%%%%%%%%%%%SSSS###%*?????%*++++?%??*********++++**?%S%SSSSSSS##SSSS%SSS%%%%%%%%%%%%%SS%SSS%\n%%%%%%%%%%%%%%%%%%%%SSSSS##%*?**%%*?+;+*?***+?%%?****+++**?%%S%SSSSSSS###SSSSSSSS%%%%%%%%%%%%%S%SSS%\n%%%SS%%%%%%%%%%%%%SSS%SS###S*?*+%%+*+;+*++*+:*%?*?*+;+++**%%%%#####SSSS###SSSSSSS%%%%%%%%%%%%%S%SSS%\n%%%%%%%%%%%%%%%%%%SSSSSSS##S****++++;;+*+;;;+++***+;;;+**?%SSS##SSSSSS%%S#SSSSSSSS%%%%%%%%%%%%%%%SS%\n%%%%%%%%%%%%%%%%%%SSSS%%SSSS*++++;;;:+*++;;;;+++++;;;;+*??%%SSS%%%SSSS#####SSSSSSS%%%%%%%%%%%%%%%%S%\n%%%%%%%%%%%%%%%%%%%%SS%SS%SS*+;;;;;;;+++++;;;;;;;;;;;++**?%SS%???S##########SSSSS%%%%%%%%%%%%%%%%%%%\n%%%%%%%%%%%%%%%%%%%%SSSSSS##?+;;;;;;+++++;;;;;;;;;;;+****??%%?*?S##############S%%%%%%%%%%%%%%%%%%%%\n%%%%%%%%%%%%%%%%%%%%%S%%S###?*+;;+;:++++++;;;;;;;;++****???%S%*%S############SS%%%%%%%%%%%%%%%%%%%%%\n%%%%%%%%%%%%%%%%%%%%%%%SSS##%*++++++*?%%??;;;;;;+++****????SS?%S%%S####SSSS###S%%%%%%%%%%%%%%%%%%%%%\n%%%%%%%%%%%%%%%%%%%%%%%SSSS#S?*+++*%%%%%?*++;;;+++****????%S*?SS*?%S###SSSSSSSS%%%%%%%%%%%%%%%%%%%%%\n%%%%%%%%%%%%%%%%%%%%%%%SSSSS#S?**?%%%?%%%?**+++++****????%S%?%S?+*%SS#####SSSSSS%%%%%%%%%%%%%%%%%%%%\n%%%%%%%%%%%%%%%%%%%%%%%%SSSSSS%%%%%%++*?%%%%%???***??????%S??S%+++%%%######SSSSS%%%%%%%%%%%%%%%%%%%%\n%%%%%%%%%%%%%%%%%%%%%%%%%SSS%%SS?*?%???*??%%???***?????%SS%?%%+;;+???%S#######SS%%%%%%%%%%%%%%%%%%%%\n%%%%%%%%%%%%%%%%%%%S%%%%%%%SSSS%*+********+++****???%%%SS%?%*;;;;+??*%%S######SS%%%%%%%%%%%%%%%%%%%%\n%%%%%%%%%%%%%%%%%%%%%%%%%%%%%SSS?***?????**++**?????%%SS%?*;::;;;+*+*??%S#SSSSS%%%%%%%%%%%%%%%%%%%%%\nS%%%%%%%%%%%%%%%SS%%%%%%%%%%%%SS%??++;;+++++**?????%%SS%*;:::;;;;++;**+?S#SSS%%%%%%%%%%%%%%%%%%%%%%%\n%%S%%%SS%SS%%%%%SS%%%%%%%%%%%%*?S%%***+++**????%?%%SS%?+:,:::::;;;;+*++?S###S%%%%%%%%%%%%%%%%%%%%%%%\nS%SS%SSSSSSSSS%SS%%%%%%%%%%%%+:+%SS?????**???%%%%SSS?*;,:::::::;;:;+;;+%#####SS%%%%%%%%%%%%%%%%%%%%%\n%%SSSSSSSSSSS%%%SS%%SSS%%%%%+:;;+%S%%%%????%?%SSS%%*;:,:::;;:::;:;;;;;?#########S%%%%%%%%%%%%%%%%%%%\nSS%S%%SSSSSSS%%%SSSS%S%%%%%+:;;+;;?SSS%???%SSSS%%*;:,::::;;;::::;;;:;*S##########SS%%%%%%%%%%%%%%%%%\nSSS%S%SSSSSSSSSSSSSSS%%SSS?::;+;;:;*%SS%%SSS%***;:,,:::;;;;:::::;::;*S#############SS%%%%%%%%%%%%%%%\n%SS%S%%SSSSSSSSSSSSSSSSS#S+::;;;;:::+%%%S%?++;;:,,::;;;;;;;::::;::;*S#################SS%%%%%%%%%%%%\n\n"}],"source":"import requests\nfrom PIL import Image\nfrom io import BytesIO\n\n# Define the ASCII characters that will be used to replace the pixels.\nASCII_CHARS = [\"@\", \"#\", \"S\", \"%\", \"?\", \"*\", \"+\", \";\", \":\", \",\", \".\"]\n\ndef resize_image(image, new_width=100):\n    width, height = image.size\n    ratio = height / width / 1.65  # Correct for aspect ratio\n    new_height = int(new_width * ratio)\n    resized_image = image.resize((new_width, new_height))\n    return resized_image\n\ndef grayify(image):\n    grayscale_image = image.convert(\"L\")\n    return grayscale_image\n\ndef pixels_to_ascii(image):\n    pixels = image.getdata()\n    ascii_str = ''\n    for pixel in pixels:\n        ascii_str += ASCII_CHARS[pixel // 25]  # Map the pixel value to ASCII_CHARS\n    return ascii_str\n\ndef process_image_from_url(image_url, new_width=100):\n    # Fetch the image from the URL\n    response = requests.get(image_url)\n    if response.status_code == 200:\n        # Open the image from the bytes in response content\n        image = Image.open(BytesIO(response.content))\n        \n        # Process the image\n        image = resize_image(image, new_width)\n        image = grayify(image)\n        ascii_str = pixels_to_ascii(image)\n\n        # Format the ASCII string so that each line has `new_width` characters.\n        img_width = image.width\n        ascii_str_len = len(ascii_str)\n        ascii_img = \"\"\n        for i in range(0, ascii_str_len, img_width):\n            ascii_img += ascii_str[i:i+img_width] + \"\\n\"\n        \n        # Print the ASCII art\n        print(ascii_img)\n    else:\n        print(\"Failed to retrieve the image from the URL\")\n\n# Example usage with a public image URL\nimage_url = 'https://i2-prod.mirror.co.uk/incoming/article7813478.ece/ALTERNATES/s1200d/William-Shakespeare.jpg'  # Replace with your image's URL\nprocess_image_from_url(image_url, 100)"},{"cell_type":"markdown","id":"df3b8c8d-3f85-4885-b090-13ed74e451a7","metadata":{"language":"python"},"source":"The participants should come up some unique Haiku or ASCII art using Notebooks. Show us how how creative you are. Join this dedicated Discord channel - https://discord.gg/re56Fwyd for any help or queries related to using Notebooks or just anything you would like to ask about the contest. "},{"cell_type":"code","execution_count":null,"id":"0fe3eeff-6476-458c-b6e2-bfde4b362b28","metadata":{"language":"python","trusted":true},"outputs":[],"source":""}],"metadata":{"jupyterlab":{"notebooks":{"version_major":6,"version_minor":4}},"kernelspec":{"display_name":"Python 3 (ipykernel)","language":"python","name":"python3"},"language_info":{"codemirror_mode":{"name":"ipython","version":3},"file_extension":".py","mimetype":"text/x-python","name":"python","nbconvert_exporter":"python","pygments_lexer":"ipython3","version":"3.11.6"},"singlestore_cell_default_language":"python","singlestore_connection":{"connectionID":"a22b6f8b-b11b-4979-98da-98513e9876e6","defaultDatabase":""}},"nbformat":4,"nbformat_minor":5}