first commit

README copy.md

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+---
+title: Avori
+emoji: 😻
+colorFrom: pink
+colorTo: gray
+sdk: gradio
+sdk_version: 3.14.0
+app_file: app.py
+pinned: false
+---
+
+Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference

api.py

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+'''''
+@author     : Ali Mustofa HALOTEC
+@module     : Service Models OCR Container Number
+@Created on : 29 Nov 2022
+'''
+import os
+import io
+import json
+import uvicorn
+from PIL import Image
+import numpy as np
+from src.process import main_process
+from fastapi import FastAPI,File
+
+app = FastAPI()
+
+@app.get("/")
+def home():
+	return {"msg": "Avocado ripe classification"}
+
+@app.post('/fruit')
+def fruit_ripe_classification(file: bytes = File(...)):
+    image = Image.open(io.BytesIO(file)).convert("RGB")
+    image = np.array(image)
+    image = image[:,:,::-1].copy()
+    result = main_process(
+        image
+    )
+    result_json = result.json()
+    return json.loads(result_json)
+
+if __name__ == '__main__':
+	uvicorn.run("api:app", host="0.0.0.0", port=8080, reload=True)
+
+
+# not_ripe = ["Medium Sea Green", "Viridian", "Medium Jungle Green", "Hooker'S Green", ]
+# almost_ripe = ["Aurometalsaurus", "Cadet Blue", "Viridian", "Payne'S Grey"]
+# almost/ripe = Hunter Green, Slate Gray
+# ripe = ["Ucla Blue", "Cadet Grey", "Dark Slate Gray", "Aurometalsaurus", "Cadet Blue", "Rackley"]
+# overripe = ["Dark Jungle Green", "Payne'S Grey", "Aurometalsaurus", "Purple Taupe", "Dim Gray", ]

app.py

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+import os
+import cv2
+import glob
+import numpy as np
+import gradio as gr
+from PIL import Image
+from src.process_gradio import main_process
+
+title = 'Avocado Ripe Classification'
+# css = ".image-preview {height: auto !important;}"
+
+inputs = [gr.inputs.Image(source='upload')]
+outputs = [gr.outputs.Image(label='image output'), gr.Label(label='Classification')]
+examples = [[f'{i}'] for i in glob.glob('images/*.jpg')]
+
+iface = gr.Interface(
+    title   = title,
+    fn      = main_process, 
+    inputs  = inputs, 
+    outputs = outputs,
+    examples= examples,
+    # css=css
+)
+
+iface.launch(share=True, server_port=8081)

colors.csv

@@ -0,0 +1,865 @@
+air_force_blue_raf,"Air Force Blue (Raf)",#5d8aa8,93,138,168
+air_force_blue_usaf,"Air Force Blue (Usaf)",#00308f,0,48,143
+air_superiority_blue,"Air Superiority Blue",#72a0c1,114,160,193
+alabama_crimson,"Alabama Crimson",#a32638,163,38,56
+alice_blue,"Alice Blue",#f0f8ff,240,248,255
+alizarin_crimson,"Alizarin Crimson",#e32636,227,38,54
+alloy_orange,"Alloy Orange",#c46210,196,98,16
+almond,"Almond",#efdecd,239,222,205
+amaranth,"Amaranth",#e52b50,229,43,80
+amber,"Amber",#ffbf00,255,191,0
+amber_sae_ece,"Amber (Sae/Ece)",#ff7e00,255,126,0
+american_rose,"American Rose",#ff033e,255,3,62
+amethyst,"Amethyst",#96c,153,102,204
+android_green,"Android Green",#a4c639,164,198,57
+anti_flash_white,"Anti-Flash White",#f2f3f4,242,243,244
+antique_brass,"Antique Brass",#cd9575,205,149,117
+antique_fuchsia,"Antique Fuchsia",#915c83,145,92,131
+antique_ruby,"Antique Ruby",#841b2d,132,27,45
+antique_white,"Antique White",#faebd7,250,235,215
+ao_english,"Ao (English)",#008000,0,128,0
+apple_green,"Apple Green",#8db600,141,182,0
+apricot,"Apricot",#fbceb1,251,206,177
+aqua,"Aqua",#0ff,0,255,255
+aquamarine,"Aquamarine",#7fffd4,127,255,212
+army_green,"Army Green",#4b5320,75,83,32
+arsenic,"Arsenic",#3b444b,59,68,75
+arylide_yellow,"Arylide Yellow",#e9d66b,233,214,107
+ash_grey,"Ash Grey",#b2beb5,178,190,181
+asparagus,"Asparagus",#87a96b,135,169,107
+atomic_tangerine,"Atomic Tangerine",#f96,255,153,102
+auburn,"Auburn",#a52a2a,165,42,42
+aureolin,"Aureolin",#fdee00,253,238,0
+aurometalsaurus,"Aurometalsaurus",#6e7f80,110,127,128
+avocado,"Avocado",#568203,86,130,3
+azure,"Azure",#007fff,0,127,255
+azure_mist_web,"Azure Mist/Web",#f0ffff,240,255,255
+baby_blue,"Baby Blue",#89cff0,137,207,240
+baby_blue_eyes,"Baby Blue Eyes",#a1caf1,161,202,241
+baby_pink,"Baby Pink",#f4c2c2,244,194,194
+ball_blue,"Ball Blue",#21abcd,33,171,205
+banana_mania,"Banana Mania",#fae7b5,250,231,181
+banana_yellow,"Banana Yellow",#ffe135,255,225,53
+barn_red,"Barn Red",#7c0a02,124,10,2
+battleship_grey,"Battleship Grey",#848482,132,132,130
+bazaar,"Bazaar",#98777b,152,119,123
+beau_blue,"Beau Blue",#bcd4e6,188,212,230
+beaver,"Beaver",#9f8170,159,129,112
+beige,"Beige",#f5f5dc,245,245,220
+big_dip_o_ruby,"Big Dip O’Ruby",#9c2542,156,37,66
+bisque,"Bisque",#ffe4c4,255,228,196
+bistre,"Bistre",#3d2b1f,61,43,31
+bittersweet,"Bittersweet",#fe6f5e,254,111,94
+bittersweet_shimmer,"Bittersweet Shimmer",#bf4f51,191,79,81
+black,"Black",#000,0,0,0
+black_bean,"Black Bean",#3d0c02,61,12,2
+black_leather_jacket,"Black Leather Jacket",#253529,37,53,41
+black_olive,"Black Olive",#3b3c36,59,60,54
+blanched_almond,"Blanched Almond",#ffebcd,255,235,205
+blast_off_bronze,"Blast-Off Bronze",#a57164,165,113,100
+bleu_de_france,"Bleu De France",#318ce7,49,140,231
+blizzard_blue,"Blizzard Blue",#ace5ee,172,229,238
+blond,"Blond",#faf0be,250,240,190
+blue,"Blue",#00f,0,0,255
+blue_bell,"Blue Bell",#a2a2d0,162,162,208
+blue_crayola,"Blue (Crayola)",#1f75fe,31,117,254
+blue_gray,"Blue Gray",#69c,102,153,204
+blue_green,"Blue-Green",#0d98ba,13,152,186
+blue_munsell,"Blue (Munsell)",#0093af,0,147,175
+blue_ncs,"Blue (Ncs)",#0087bd,0,135,189
+blue_pigment,"Blue (Pigment)",#339,51,51,153
+blue_ryb,"Blue (Ryb)",#0247fe,2,71,254
+blue_sapphire,"Blue Sapphire",#126180,18,97,128
+blue_violet,"Blue-Violet",#8a2be2,138,43,226
+blush,"Blush",#de5d83,222,93,131
+bole,"Bole",#79443b,121,68,59
+bondi_blue,"Bondi Blue",#0095b6,0,149,182
+bone,"Bone",#e3dac9,227,218,201
+boston_university_red,"Boston University Red",#c00,204,0,0
+bottle_green,"Bottle Green",#006a4e,0,106,78
+boysenberry,"Boysenberry",#873260,135,50,96
+brandeis_blue,"Brandeis Blue",#0070ff,0,112,255
+brass,"Brass",#b5a642,181,166,66
+brick_red,"Brick Red",#cb4154,203,65,84
+bright_cerulean,"Bright Cerulean",#1dacd6,29,172,214
+bright_green,"Bright Green",#6f0,102,255,0
+bright_lavender,"Bright Lavender",#bf94e4,191,148,228
+bright_maroon,"Bright Maroon",#c32148,195,33,72
+bright_pink,"Bright Pink",#ff007f,255,0,127
+bright_turquoise,"Bright Turquoise",#08e8de,8,232,222
+bright_ube,"Bright Ube",#d19fe8,209,159,232
+brilliant_lavender,"Brilliant Lavender",#f4bbff,244,187,255
+brilliant_rose,"Brilliant Rose",#ff55a3,255,85,163
+brink_pink,"Brink Pink",#fb607f,251,96,127
+british_racing_green,"British Racing Green",#004225,0,66,37
+bronze,"Bronze",#cd7f32,205,127,50
+brown_traditional,"Brown (Traditional)",#964b00,150,75,0
+brown_web,"Brown (Web)",#a52a2a,165,42,42
+bubble_gum,"Bubble Gum",#ffc1cc,255,193,204
+bubbles,"Bubbles",#e7feff,231,254,255
+buff,"Buff",#f0dc82,240,220,130
+bulgarian_rose,"Bulgarian Rose",#480607,72,6,7
+burgundy,"Burgundy",#800020,128,0,32
+burlywood,"Burlywood",#deb887,222,184,135
+burnt_orange,"Burnt Orange",#c50,204,85,0
+burnt_sienna,"Burnt Sienna",#e97451,233,116,81
+burnt_umber,"Burnt Umber",#8a3324,138,51,36
+byzantine,"Byzantine",#bd33a4,189,51,164
+byzantium,"Byzantium",#702963,112,41,99
+cadet,"Cadet",#536872,83,104,114
+cadet_blue,"Cadet Blue",#5f9ea0,95,158,160
+cadet_grey,"Cadet Grey",#91a3b0,145,163,176
+cadmium_green,"Cadmium Green",#006b3c,0,107,60
+cadmium_orange,"Cadmium Orange",#ed872d,237,135,45
+cadmium_red,"Cadmium Red",#e30022,227,0,34
+cadmium_yellow,"Cadmium Yellow",#fff600,255,246,0
+caf_au_lait,"Café Au Lait",#a67b5b,166,123,91
+caf_noir,"Café Noir",#4b3621,75,54,33
+cal_poly_green,"Cal Poly Green",#1e4d2b,30,77,43
+cambridge_blue,"Cambridge Blue",#a3c1ad,163,193,173
+camel,"Camel",#c19a6b,193,154,107
+cameo_pink,"Cameo Pink",#efbbcc,239,187,204
+camouflage_green,"Camouflage Green",#78866b,120,134,107
+canary_yellow,"Canary Yellow",#ffef00,255,239,0
+candy_apple_red,"Candy Apple Red",#ff0800,255,8,0
+candy_pink,"Candy Pink",#e4717a,228,113,122
+capri,"Capri",#00bfff,0,191,255
+caput_mortuum,"Caput Mortuum",#592720,89,39,32
+cardinal,"Cardinal",#c41e3a,196,30,58
+caribbean_green,"Caribbean Green",#0c9,0,204,153
+carmine,"Carmine",#960018,150,0,24
+carmine_m_p,"Carmine (M&P)",#d70040,215,0,64
+carmine_pink,"Carmine Pink",#eb4c42,235,76,66
+carmine_red,"Carmine Red",#ff0038,255,0,56
+carnation_pink,"Carnation Pink",#ffa6c9,255,166,201
+carnelian,"Carnelian",#b31b1b,179,27,27
+carolina_blue,"Carolina Blue",#99badd,153,186,221
+carrot_orange,"Carrot Orange",#ed9121,237,145,33
+catalina_blue,"Catalina Blue",#062a78,6,42,120
+ceil,"Ceil",#92a1cf,146,161,207
+celadon,"Celadon",#ace1af,172,225,175
+celadon_blue,"Celadon Blue",#007ba7,0,123,167
+celadon_green,"Celadon Green",#2f847c,47,132,124
+celeste_colour,"Celeste (Colour)",#b2ffff,178,255,255
+celestial_blue,"Celestial Blue",#4997d0,73,151,208
+cerise,"Cerise",#de3163,222,49,99
+cerise_pink,"Cerise Pink",#ec3b83,236,59,131
+cerulean,"Cerulean",#007ba7,0,123,167
+cerulean_blue,"Cerulean Blue",#2a52be,42,82,190
+cerulean_frost,"Cerulean Frost",#6d9bc3,109,155,195
+cg_blue,"Cg Blue",#007aa5,0,122,165
+cg_red,"Cg Red",#e03c31,224,60,49
+chamoisee,"Chamoisee",#a0785a,160,120,90
+champagne,"Champagne",#fad6a5,250,214,165
+charcoal,"Charcoal",#36454f,54,69,79
+charm_pink,"Charm Pink",#e68fac,230,143,172
+chartreuse_traditional,"Chartreuse (Traditional)",#dfff00,223,255,0
+chartreuse_web,"Chartreuse (Web)",#7fff00,127,255,0
+cherry,"Cherry",#de3163,222,49,99
+cherry_blossom_pink,"Cherry Blossom Pink",#ffb7c5,255,183,197
+chestnut,"Chestnut",#cd5c5c,205,92,92
+china_pink,"China Pink",#de6fa1,222,111,161
+china_rose,"China Rose",#a8516e,168,81,110
+chinese_red,"Chinese Red",#aa381e,170,56,30
+chocolate_traditional,"Chocolate (Traditional)",#7b3f00,123,63,0
+chocolate_web,"Chocolate (Web)",#d2691e,210,105,30
+chrome_yellow,"Chrome Yellow",#ffa700,255,167,0
+cinereous,"Cinereous",#98817b,152,129,123
+cinnabar,"Cinnabar",#e34234,227,66,52
+cinnamon,"Cinnamon",#d2691e,210,105,30
+citrine,"Citrine",#e4d00a,228,208,10
+classic_rose,"Classic Rose",#fbcce7,251,204,231
+cobalt,"Cobalt",#0047ab,0,71,171
+cocoa_brown,"Cocoa Brown",#d2691e,210,105,30
+coffee,"Coffee",#6f4e37,111,78,55
+columbia_blue,"Columbia Blue",#9bddff,155,221,255
+congo_pink,"Congo Pink",#f88379,248,131,121
+cool_black,"Cool Black",#002e63,0,46,99
+cool_grey,"Cool Grey",#8c92ac,140,146,172
+copper,"Copper",#b87333,184,115,51
+copper_crayola,"Copper (Crayola)",#da8a67,218,138,103
+copper_penny,"Copper Penny",#ad6f69,173,111,105
+copper_red,"Copper Red",#cb6d51,203,109,81
+copper_rose,"Copper Rose",#966,153,102,102
+coquelicot,"Coquelicot",#ff3800,255,56,0
+coral,"Coral",#ff7f50,255,127,80
+coral_pink,"Coral Pink",#f88379,248,131,121
+coral_red,"Coral Red",#ff4040,255,64,64
+cordovan,"Cordovan",#893f45,137,63,69
+corn,"Corn",#fbec5d,251,236,93
+cornell_red,"Cornell Red",#b31b1b,179,27,27
+cornflower_blue,"Cornflower Blue",#6495ed,100,149,237
+cornsilk,"Cornsilk",#fff8dc,255,248,220
+cosmic_latte,"Cosmic Latte",#fff8e7,255,248,231
+cotton_candy,"Cotton Candy",#ffbcd9,255,188,217
+cream,"Cream",#fffdd0,255,253,208
+crimson,"Crimson",#dc143c,220,20,60
+crimson_glory,"Crimson Glory",#be0032,190,0,50
+cyan,"Cyan",#0ff,0,255,255
+cyan_process,"Cyan (Process)",#00b7eb,0,183,235
+daffodil,"Daffodil",#ffff31,255,255,49
+dandelion,"Dandelion",#f0e130,240,225,48
+dark_blue,"Dark Blue",#00008b,0,0,139
+dark_brown,"Dark Brown",#654321,101,67,33
+dark_byzantium,"Dark Byzantium",#5d3954,93,57,84
+dark_candy_apple_red,"Dark Candy Apple Red",#a40000,164,0,0
+dark_cerulean,"Dark Cerulean",#08457e,8,69,126
+dark_chestnut,"Dark Chestnut",#986960,152,105,96
+dark_coral,"Dark Coral",#cd5b45,205,91,69
+dark_cyan,"Dark Cyan",#008b8b,0,139,139
+dark_electric_blue,"Dark Electric Blue",#536878,83,104,120
+dark_goldenrod,"Dark Goldenrod",#b8860b,184,134,11
+dark_gray,"Dark Gray",#a9a9a9,169,169,169
+dark_green,"Dark Green",#013220,1,50,32
+dark_imperial_blue,"Dark Imperial Blue",#00416a,0,65,106
+dark_jungle_green,"Dark Jungle Green",#1a2421,26,36,33
+dark_khaki,"Dark Khaki",#bdb76b,189,183,107
+dark_lava,"Dark Lava",#483c32,72,60,50
+dark_lavender,"Dark Lavender",#734f96,115,79,150
+dark_magenta,"Dark Magenta",#8b008b,139,0,139
+dark_midnight_blue,"Dark Midnight Blue",#036,0,51,102
+dark_olive_green,"Dark Olive Green",#556b2f,85,107,47
+dark_orange,"Dark Orange",#ff8c00,255,140,0
+dark_orchid,"Dark Orchid",#9932cc,153,50,204
+dark_pastel_blue,"Dark Pastel Blue",#779ecb,119,158,203
+dark_pastel_green,"Dark Pastel Green",#03c03c,3,192,60
+dark_pastel_purple,"Dark Pastel Purple",#966fd6,150,111,214
+dark_pastel_red,"Dark Pastel Red",#c23b22,194,59,34
+dark_pink,"Dark Pink",#e75480,231,84,128
+dark_powder_blue,"Dark Powder Blue",#039,0,51,153
+dark_raspberry,"Dark Raspberry",#872657,135,38,87
+dark_red,"Dark Red",#8b0000,139,0,0
+dark_salmon,"Dark Salmon",#e9967a,233,150,122
+dark_scarlet,"Dark Scarlet",#560319,86,3,25
+dark_sea_green,"Dark Sea Green",#8fbc8f,143,188,143
+dark_sienna,"Dark Sienna",#3c1414,60,20,20
+dark_slate_blue,"Dark Slate Blue",#483d8b,72,61,139
+dark_slate_gray,"Dark Slate Gray",#2f4f4f,47,79,79
+dark_spring_green,"Dark Spring Green",#177245,23,114,69
+dark_tan,"Dark Tan",#918151,145,129,81
+dark_tangerine,"Dark Tangerine",#ffa812,255,168,18
+dark_taupe,"Dark Taupe",#483c32,72,60,50
+dark_terra_cotta,"Dark Terra Cotta",#cc4e5c,204,78,92
+dark_turquoise,"Dark Turquoise",#00ced1,0,206,209
+dark_violet,"Dark Violet",#9400d3,148,0,211
+dark_yellow,"Dark Yellow",#9b870c,155,135,12
+dartmouth_green,"Dartmouth Green",#00703c,0,112,60
+davy_s_grey,"Davy'S Grey",#555,85,85,85
+debian_red,"Debian Red",#d70a53,215,10,83
+deep_carmine,"Deep Carmine",#a9203e,169,32,62
+deep_carmine_pink,"Deep Carmine Pink",#ef3038,239,48,56
+deep_carrot_orange,"Deep Carrot Orange",#e9692c,233,105,44
+deep_cerise,"Deep Cerise",#da3287,218,50,135
+deep_champagne,"Deep Champagne",#fad6a5,250,214,165
+deep_chestnut,"Deep Chestnut",#b94e48,185,78,72
+deep_coffee,"Deep Coffee",#704241,112,66,65
+deep_fuchsia,"Deep Fuchsia",#c154c1,193,84,193
+deep_jungle_green,"Deep Jungle Green",#004b49,0,75,73
+deep_lilac,"Deep Lilac",#95b,153,85,187
+deep_magenta,"Deep Magenta",#c0c,204,0,204
+deep_peach,"Deep Peach",#ffcba4,255,203,164
+deep_pink,"Deep Pink",#ff1493,255,20,147
+deep_ruby,"Deep Ruby",#843f5b,132,63,91
+deep_saffron,"Deep Saffron",#f93,255,153,51
+deep_sky_blue,"Deep Sky Blue",#00bfff,0,191,255
+deep_tuscan_red,"Deep Tuscan Red",#66424d,102,66,77
+denim,"Denim",#1560bd,21,96,189
+desert,"Desert",#c19a6b,193,154,107
+desert_sand,"Desert Sand",#edc9af,237,201,175
+dim_gray,"Dim Gray",#696969,105,105,105
+dodger_blue,"Dodger Blue",#1e90ff,30,144,255
+dogwood_rose,"Dogwood Rose",#d71868,215,24,104
+dollar_bill,"Dollar Bill",#85bb65,133,187,101
+drab,"Drab",#967117,150,113,23
+duke_blue,"Duke Blue",#00009c,0,0,156
+earth_yellow,"Earth Yellow",#e1a95f,225,169,95
+ebony,"Ebony",#555d50,85,93,80
+ecru,"Ecru",#c2b280,194,178,128
+eggplant,"Eggplant",#614051,97,64,81
+eggshell,"Eggshell",#f0ead6,240,234,214
+egyptian_blue,"Egyptian Blue",#1034a6,16,52,166
+electric_blue,"Electric Blue",#7df9ff,125,249,255
+electric_crimson,"Electric Crimson",#ff003f,255,0,63
+electric_cyan,"Electric Cyan",#0ff,0,255,255
+electric_green,"Electric Green",#0f0,0,255,0
+electric_indigo,"Electric Indigo",#6f00ff,111,0,255
+electric_lavender,"Electric Lavender",#f4bbff,244,187,255
+electric_lime,"Electric Lime",#cf0,204,255,0
+electric_purple,"Electric Purple",#bf00ff,191,0,255
+electric_ultramarine,"Electric Ultramarine",#3f00ff,63,0,255
+electric_violet,"Electric Violet",#8f00ff,143,0,255
+electric_yellow,"Electric Yellow",#ff0,255,255,0
+emerald,"Emerald",#50c878,80,200,120
+english_lavender,"English Lavender",#b48395,180,131,149
+eton_blue,"Eton Blue",#96c8a2,150,200,162
+fallow,"Fallow",#c19a6b,193,154,107
+falu_red,"Falu Red",#801818,128,24,24
+fandango,"Fandango",#b53389,181,51,137
+fashion_fuchsia,"Fashion Fuchsia",#f400a1,244,0,161
+fawn,"Fawn",#e5aa70,229,170,112
+feldgrau,"Feldgrau",#4d5d53,77,93,83
+fern_green,"Fern Green",#4f7942,79,121,66
+ferrari_red,"Ferrari Red",#ff2800,255,40,0
+field_drab,"Field Drab",#6c541e,108,84,30
+fire_engine_red,"Fire Engine Red",#ce2029,206,32,41
+firebrick,"Firebrick",#b22222,178,34,34
+flame,"Flame",#e25822,226,88,34
+flamingo_pink,"Flamingo Pink",#fc8eac,252,142,172
+flavescent,"Flavescent",#f7e98e,247,233,142
+flax,"Flax",#eedc82,238,220,130
+floral_white,"Floral White",#fffaf0,255,250,240
+fluorescent_orange,"Fluorescent Orange",#ffbf00,255,191,0
+fluorescent_pink,"Fluorescent Pink",#ff1493,255,20,147
+fluorescent_yellow,"Fluorescent Yellow",#cf0,204,255,0
+folly,"Folly",#ff004f,255,0,79
+forest_green_traditional,"Forest Green (Traditional)",#014421,1,68,33
+forest_green_web,"Forest Green (Web)",#228b22,34,139,34
+french_beige,"French Beige",#a67b5b,166,123,91
+french_blue,"French Blue",#0072bb,0,114,187
+french_lilac,"French Lilac",#86608e,134,96,142
+french_lime,"French Lime",#cf0,204,255,0
+french_raspberry,"French Raspberry",#c72c48,199,44,72
+french_rose,"French Rose",#f64a8a,246,74,138
+fuchsia,"Fuchsia",#f0f,255,0,255
+fuchsia_crayola,"Fuchsia (Crayola)",#c154c1,193,84,193
+fuchsia_pink,"Fuchsia Pink",#f7f,255,119,255
+fuchsia_rose,"Fuchsia Rose",#c74375,199,67,117
+fulvous,"Fulvous",#e48400,228,132,0
+fuzzy_wuzzy,"Fuzzy Wuzzy",#c66,204,102,102
+gainsboro,"Gainsboro",#dcdcdc,220,220,220
+gamboge,"Gamboge",#e49b0f,228,155,15
+ghost_white,"Ghost White",#f8f8ff,248,248,255
+ginger,"Ginger",#b06500,176,101,0
+glaucous,"Glaucous",#6082b6,96,130,182
+glitter,"Glitter",#e6e8fa,230,232,250
+gold_metallic,"Gold (Metallic)",#d4af37,212,175,55
+gold_web_golden,"Gold (Web) (Golden)",#ffd700,255,215,0
+golden_brown,"Golden Brown",#996515,153,101,21
+golden_poppy,"Golden Poppy",#fcc200,252,194,0
+golden_yellow,"Golden Yellow",#ffdf00,255,223,0
+goldenrod,"Goldenrod",#daa520,218,165,32
+granny_smith_apple,"Granny Smith Apple",#a8e4a0,168,228,160
+gray,"Gray",#808080,128,128,128
+gray_asparagus,"Gray-Asparagus",#465945,70,89,69
+gray_html_css_gray,"Gray (Html/Css Gray)",#808080,128,128,128
+gray_x11_gray,"Gray (X11 Gray)",#bebebe,190,190,190
+green_color_wheel_x11_green,"Green (Color Wheel) (X11 Green)",#0f0,0,255,0
+green_crayola,"Green (Crayola)",#1cac78,28,172,120
+green_html_css_green,"Green (Html/Css Green)",#008000,0,128,0
+green_munsell,"Green (Munsell)",#00a877,0,168,119
+green_ncs,"Green (Ncs)",#009f6b,0,159,107
+green_pigment,"Green (Pigment)",#00a550,0,165,80
+green_ryb,"Green (Ryb)",#66b032,102,176,50
+green_yellow,"Green-Yellow",#adff2f,173,255,47
+grullo,"Grullo",#a99a86,169,154,134
+guppie_green,"Guppie Green",#00ff7f,0,255,127
+halay_be,"Halayà úBe",#663854,102,56,84
+han_blue,"Han Blue",#446ccf,68,108,207
+han_purple,"Han Purple",#5218fa,82,24,250
+hansa_yellow,"Hansa Yellow",#e9d66b,233,214,107
+harlequin,"Harlequin",#3fff00,63,255,0
+harvard_crimson,"Harvard Crimson",#c90016,201,0,22
+harvest_gold,"Harvest Gold",#da9100,218,145,0
+heart_gold,"Heart Gold",#808000,128,128,0
+heliotrope,"Heliotrope",#df73ff,223,115,255
+hollywood_cerise,"Hollywood Cerise",#f400a1,244,0,161
+honeydew,"Honeydew",#f0fff0,240,255,240
+honolulu_blue,"Honolulu Blue",#007fbf,0,127,191
+hooker_s_green,"Hooker'S Green",#49796b,73,121,107
+hot_magenta,"Hot Magenta",#ff1dce,255,29,206
+hot_pink,"Hot Pink",#ff69b4,255,105,180
+hunter_green,"Hunter Green",#355e3b,53,94,59
+iceberg,"Iceberg",#71a6d2,113,166,210
+icterine,"Icterine",#fcf75e,252,247,94
+imperial_blue,"Imperial Blue",#002395,0,35,149
+inchworm,"Inchworm",#b2ec5d,178,236,93
+india_green,"India Green",#138808,19,136,8
+indian_red,"Indian Red",#cd5c5c,205,92,92
+indian_yellow,"Indian Yellow",#e3a857,227,168,87
+indigo,"Indigo",#6f00ff,111,0,255
+indigo_dye,"Indigo (Dye)",#00416a,0,65,106
+indigo_web,"Indigo (Web)",#4b0082,75,0,130
+international_klein_blue,"International Klein Blue",#002fa7,0,47,167
+international_orange_aerospace,"International Orange (Aerospace)",#ff4f00,255,79,0
+international_orange_engineering,"International Orange (Engineering)",#ba160c,186,22,12
+international_orange_golden_gate_bridge,"International Orange (Golden Gate Bridge)",#c0362c,192,54,44
+iris,"Iris",#5a4fcf,90,79,207
+isabelline,"Isabelline",#f4f0ec,244,240,236
+islamic_green,"Islamic Green",#009000,0,144,0
+ivory,"Ivory",#fffff0,255,255,240
+jade,"Jade",#00a86b,0,168,107
+jasmine,"Jasmine",#f8de7e,248,222,126
+jasper,"Jasper",#d73b3e,215,59,62
+jazzberry_jam,"Jazzberry Jam",#a50b5e,165,11,94
+jet,"Jet",#343434,52,52,52
+jonquil,"Jonquil",#fada5e,250,218,94
+june_bud,"June Bud",#bdda57,189,218,87
+jungle_green,"Jungle Green",#29ab87,41,171,135
+kelly_green,"Kelly Green",#4cbb17,76,187,23
+kenyan_copper,"Kenyan Copper",#7c1c05,124,28,5
+khaki_html_css_khaki,"Khaki (Html/Css) (Khaki)",#c3b091,195,176,145
+khaki_x11_light_khaki,"Khaki (X11) (Light Khaki)",#f0e68c,240,230,140
+ku_crimson,"Ku Crimson",#e8000d,232,0,13
+la_salle_green,"La Salle Green",#087830,8,120,48
+languid_lavender,"Languid Lavender",#d6cadd,214,202,221
+lapis_lazuli,"Lapis Lazuli",#26619c,38,97,156
+laser_lemon,"Laser Lemon",#fefe22,254,254,34
+laurel_green,"Laurel Green",#a9ba9d,169,186,157
+lava,"Lava",#cf1020,207,16,32
+lavender_blue,"Lavender Blue",#ccf,204,204,255
+lavender_blush,"Lavender Blush",#fff0f5,255,240,245
+lavender_floral,"Lavender (Floral)",#b57edc,181,126,220
+lavender_gray,"Lavender Gray",#c4c3d0,196,195,208
+lavender_indigo,"Lavender Indigo",#9457eb,148,87,235
+lavender_magenta,"Lavender Magenta",#ee82ee,238,130,238
+lavender_mist,"Lavender Mist",#e6e6fa,230,230,250
+lavender_pink,"Lavender Pink",#fbaed2,251,174,210
+lavender_purple,"Lavender Purple",#967bb6,150,123,182
+lavender_rose,"Lavender Rose",#fba0e3,251,160,227
+lavender_web,"Lavender (Web)",#e6e6fa,230,230,250
+lawn_green,"Lawn Green",#7cfc00,124,252,0
+lemon,"Lemon",#fff700,255,247,0
+lemon_chiffon,"Lemon Chiffon",#fffacd,255,250,205
+lemon_lime,"Lemon Lime",#e3ff00,227,255,0
+licorice,"Licorice",#1a1110,26,17,16
+light_apricot,"Light Apricot",#fdd5b1,253,213,177
+light_blue,"Light Blue",#add8e6,173,216,230
+light_brown,"Light Brown",#b5651d,181,101,29
+light_carmine_pink,"Light Carmine Pink",#e66771,230,103,113
+light_coral,"Light Coral",#f08080,240,128,128
+light_cornflower_blue,"Light Cornflower Blue",#93ccea,147,204,234
+light_crimson,"Light Crimson",#f56991,245,105,145
+light_cyan,"Light Cyan",#e0ffff,224,255,255
+light_fuchsia_pink,"Light Fuchsia Pink",#f984ef,249,132,239
+light_goldenrod_yellow,"Light Goldenrod Yellow",#fafad2,250,250,210
+light_gray,"Light Gray",#d3d3d3,211,211,211
+light_green,"Light Green",#90ee90,144,238,144
+light_khaki,"Light Khaki",#f0e68c,240,230,140
+light_pastel_purple,"Light Pastel Purple",#b19cd9,177,156,217
+light_pink,"Light Pink",#ffb6c1,255,182,193
+light_red_ochre,"Light Red Ochre",#e97451,233,116,81
+light_salmon,"Light Salmon",#ffa07a,255,160,122
+light_salmon_pink,"Light Salmon Pink",#f99,255,153,153
+light_sea_green,"Light Sea Green",#20b2aa,32,178,170
+light_sky_blue,"Light Sky Blue",#87cefa,135,206,250
+light_slate_gray,"Light Slate Gray",#789,119,136,153
+light_taupe,"Light Taupe",#b38b6d,179,139,109
+light_thulian_pink,"Light Thulian Pink",#e68fac,230,143,172
+light_yellow,"Light Yellow",#ffffe0,255,255,224
+lilac,"Lilac",#c8a2c8,200,162,200
+lime_color_wheel,"Lime (Color Wheel)",#bfff00,191,255,0
+lime_green,"Lime Green",#32cd32,50,205,50
+lime_web_x11_green,"Lime (Web) (X11 Green)",#0f0,0,255,0
+limerick,"Limerick",#9dc209,157,194,9
+lincoln_green,"Lincoln Green",#195905,25,89,5
+linen,"Linen",#faf0e6,250,240,230
+lion,"Lion",#c19a6b,193,154,107
+little_boy_blue,"Little Boy Blue",#6ca0dc,108,160,220
+liver,"Liver",#534b4f,83,75,79
+lust,"Lust",#e62020,230,32,32
+magenta,"Magenta",#f0f,255,0,255
+magenta_dye,"Magenta (Dye)",#ca1f7b,202,31,123
+magenta_process,"Magenta (Process)",#ff0090,255,0,144
+magic_mint,"Magic Mint",#aaf0d1,170,240,209
+magnolia,"Magnolia",#f8f4ff,248,244,255
+mahogany,"Mahogany",#c04000,192,64,0
+maize,"Maize",#fbec5d,251,236,93
+majorelle_blue,"Majorelle Blue",#6050dc,96,80,220
+malachite,"Malachite",#0bda51,11,218,81
+manatee,"Manatee",#979aaa,151,154,170
+mango_tango,"Mango Tango",#ff8243,255,130,67
+mantis,"Mantis",#74c365,116,195,101
+mardi_gras,"Mardi Gras",#880085,136,0,133
+maroon_crayola,"Maroon (Crayola)",#c32148,195,33,72
+maroon_html_css,"Maroon (Html/Css)",#800000,128,0,0
+maroon_x11,"Maroon (X11)",#b03060,176,48,96
+mauve,"Mauve",#e0b0ff,224,176,255
+mauve_taupe,"Mauve Taupe",#915f6d,145,95,109
+mauvelous,"Mauvelous",#ef98aa,239,152,170
+maya_blue,"Maya Blue",#73c2fb,115,194,251
+meat_brown,"Meat Brown",#e5b73b,229,183,59
+medium_aquamarine,"Medium Aquamarine",#6da,102,221,170
+medium_blue,"Medium Blue",#0000cd,0,0,205
+medium_candy_apple_red,"Medium Candy Apple Red",#e2062c,226,6,44
+medium_carmine,"Medium Carmine",#af4035,175,64,53
+medium_champagne,"Medium Champagne",#f3e5ab,243,229,171
+medium_electric_blue,"Medium Electric Blue",#035096,3,80,150
+medium_jungle_green,"Medium Jungle Green",#1c352d,28,53,45
+medium_lavender_magenta,"Medium Lavender Magenta",#dda0dd,221,160,221
+medium_orchid,"Medium Orchid",#ba55d3,186,85,211
+medium_persian_blue,"Medium Persian Blue",#0067a5,0,103,165
+medium_purple,"Medium Purple",#9370db,147,112,219
+medium_red_violet,"Medium Red-Violet",#bb3385,187,51,133
+medium_ruby,"Medium Ruby",#aa4069,170,64,105
+medium_sea_green,"Medium Sea Green",#3cb371,60,179,113
+medium_slate_blue,"Medium Slate Blue",#7b68ee,123,104,238
+medium_spring_bud,"Medium Spring Bud",#c9dc87,201,220,135
+medium_spring_green,"Medium Spring Green",#00fa9a,0,250,154
+medium_taupe,"Medium Taupe",#674c47,103,76,71
+medium_turquoise,"Medium Turquoise",#48d1cc,72,209,204
+medium_tuscan_red,"Medium Tuscan Red",#79443b,121,68,59
+medium_vermilion,"Medium Vermilion",#d9603b,217,96,59
+medium_violet_red,"Medium Violet-Red",#c71585,199,21,133
+mellow_apricot,"Mellow Apricot",#f8b878,248,184,120
+mellow_yellow,"Mellow Yellow",#f8de7e,248,222,126
+melon,"Melon",#fdbcb4,253,188,180
+midnight_blue,"Midnight Blue",#191970,25,25,112
+midnight_green_eagle_green,"Midnight Green (Eagle Green)",#004953,0,73,83
+mikado_yellow,"Mikado Yellow",#ffc40c,255,196,12
+mint,"Mint",#3eb489,62,180,137
+mint_cream,"Mint Cream",#f5fffa,245,255,250
+mint_green,"Mint Green",#98ff98,152,255,152
+misty_rose,"Misty Rose",#ffe4e1,255,228,225
+moccasin,"Moccasin",#faebd7,250,235,215
+mode_beige,"Mode Beige",#967117,150,113,23
+moonstone_blue,"Moonstone Blue",#73a9c2,115,169,194
+mordant_red_19,"Mordant Red 19",#ae0c00,174,12,0
+moss_green,"Moss Green",#addfad,173,223,173
+mountain_meadow,"Mountain Meadow",#30ba8f,48,186,143
+mountbatten_pink,"Mountbatten Pink",#997a8d,153,122,141
+msu_green,"Msu Green",#18453b,24,69,59
+mulberry,"Mulberry",#c54b8c,197,75,140
+mustard,"Mustard",#ffdb58,255,219,88
+myrtle,"Myrtle",#21421e,33,66,30
+nadeshiko_pink,"Nadeshiko Pink",#f6adc6,246,173,198
+napier_green,"Napier Green",#2a8000,42,128,0
+naples_yellow,"Naples Yellow",#fada5e,250,218,94
+navajo_white,"Navajo White",#ffdead,255,222,173
+navy_blue,"Navy Blue",#000080,0,0,128
+neon_carrot,"Neon Carrot",#ffa343,255,163,67
+neon_fuchsia,"Neon Fuchsia",#fe4164,254,65,100
+neon_green,"Neon Green",#39ff14,57,255,20
+new_york_pink,"New York Pink",#d7837f,215,131,127
+non_photo_blue,"Non-Photo Blue",#a4dded,164,221,237
+north_texas_green,"North Texas Green",#059033,5,144,51
+ocean_boat_blue,"Ocean Boat Blue",#0077be,0,119,190
+ochre,"Ochre",#c72,204,119,34
+office_green,"Office Green",#008000,0,128,0
+old_gold,"Old Gold",#cfb53b,207,181,59
+old_lace,"Old Lace",#fdf5e6,253,245,230
+old_lavender,"Old Lavender",#796878,121,104,120
+old_mauve,"Old Mauve",#673147,103,49,71
+old_rose,"Old Rose",#c08081,192,128,129
+olive,"Olive",#808000,128,128,0
+olive_drab_7,"Olive Drab #7",#3c341f,60,52,31
+olive_drab_web_olive_drab_3,"Olive Drab (Web) (Olive Drab #3)",#6b8e23,107,142,35
+olivine,"Olivine",#9ab973,154,185,115
+onyx,"Onyx",#353839,53,56,57
+opera_mauve,"Opera Mauve",#b784a7,183,132,167
+orange_color_wheel,"Orange (Color Wheel)",#ff7f00,255,127,0
+orange_peel,"Orange Peel",#ff9f00,255,159,0
+orange_red,"Orange-Red",#ff4500,255,69,0
+orange_ryb,"Orange (Ryb)",#fb9902,251,153,2
+orange_web_color,"Orange (Web Color)",#ffa500,255,165,0
+orchid,"Orchid",#da70d6,218,112,214
+otter_brown,"Otter Brown",#654321,101,67,33
+ou_crimson_red,"Ou Crimson Red",#900,153,0,0
+outer_space,"Outer Space",#414a4c,65,74,76
+outrageous_orange,"Outrageous Orange",#ff6e4a,255,110,74
+oxford_blue,"Oxford Blue",#002147,0,33,71
+pakistan_green,"Pakistan Green",#060,0,102,0
+palatinate_blue,"Palatinate Blue",#273be2,39,59,226
+palatinate_purple,"Palatinate Purple",#682860,104,40,96
+pale_aqua,"Pale Aqua",#bcd4e6,188,212,230
+pale_blue,"Pale Blue",#afeeee,175,238,238
+pale_brown,"Pale Brown",#987654,152,118,84
+pale_carmine,"Pale Carmine",#af4035,175,64,53
+pale_cerulean,"Pale Cerulean",#9bc4e2,155,196,226
+pale_chestnut,"Pale Chestnut",#ddadaf,221,173,175
+pale_copper,"Pale Copper",#da8a67,218,138,103
+pale_cornflower_blue,"Pale Cornflower Blue",#abcdef,171,205,239
+pale_gold,"Pale Gold",#e6be8a,230,190,138
+pale_goldenrod,"Pale Goldenrod",#eee8aa,238,232,170
+pale_green,"Pale Green",#98fb98,152,251,152
+pale_lavender,"Pale Lavender",#dcd0ff,220,208,255
+pale_magenta,"Pale Magenta",#f984e5,249,132,229
+pale_pink,"Pale Pink",#fadadd,250,218,221
+pale_plum,"Pale Plum",#dda0dd,221,160,221
+pale_red_violet,"Pale Red-Violet",#db7093,219,112,147
+pale_robin_egg_blue,"Pale Robin Egg Blue",#96ded1,150,222,209
+pale_silver,"Pale Silver",#c9c0bb,201,192,187
+pale_spring_bud,"Pale Spring Bud",#ecebbd,236,235,189
+pale_taupe,"Pale Taupe",#bc987e,188,152,126
+pale_violet_red,"Pale Violet-Red",#db7093,219,112,147
+pansy_purple,"Pansy Purple",#78184a,120,24,74
+papaya_whip,"Papaya Whip",#ffefd5,255,239,213
+paris_green,"Paris Green",#50c878,80,200,120
+pastel_blue,"Pastel Blue",#aec6cf,174,198,207
+pastel_brown,"Pastel Brown",#836953,131,105,83
+pastel_gray,"Pastel Gray",#cfcfc4,207,207,196
+pastel_green,"Pastel Green",#7d7,119,221,119
+pastel_magenta,"Pastel Magenta",#f49ac2,244,154,194
+pastel_orange,"Pastel Orange",#ffb347,255,179,71
+pastel_pink,"Pastel Pink",#dea5a4,222,165,164
+pastel_purple,"Pastel Purple",#b39eb5,179,158,181
+pastel_red,"Pastel Red",#ff6961,255,105,97
+pastel_violet,"Pastel Violet",#cb99c9,203,153,201
+pastel_yellow,"Pastel Yellow",#fdfd96,253,253,150
+patriarch,"Patriarch",#800080,128,0,128
+payne_s_grey,"Payne'S Grey",#536878,83,104,120
+peach,"Peach",#ffe5b4,255,229,180
+peach_crayola,"Peach (Crayola)",#ffcba4,255,203,164
+peach_orange,"Peach-Orange",#fc9,255,204,153
+peach_puff,"Peach Puff",#ffdab9,255,218,185
+peach_yellow,"Peach-Yellow",#fadfad,250,223,173
+pear,"Pear",#d1e231,209,226,49
+pearl,"Pearl",#eae0c8,234,224,200
+pearl_aqua,"Pearl Aqua",#88d8c0,136,216,192
+pearly_purple,"Pearly Purple",#b768a2,183,104,162
+peridot,"Peridot",#e6e200,230,226,0
+periwinkle,"Periwinkle",#ccf,204,204,255
+persian_blue,"Persian Blue",#1c39bb,28,57,187
+persian_green,"Persian Green",#00a693,0,166,147
+persian_indigo,"Persian Indigo",#32127a,50,18,122
+persian_orange,"Persian Orange",#d99058,217,144,88
+persian_pink,"Persian Pink",#f77fbe,247,127,190
+persian_plum,"Persian Plum",#701c1c,112,28,28
+persian_red,"Persian Red",#c33,204,51,51
+persian_rose,"Persian Rose",#fe28a2,254,40,162
+persimmon,"Persimmon",#ec5800,236,88,0
+peru,"Peru",#cd853f,205,133,63
+phlox,"Phlox",#df00ff,223,0,255
+phthalo_blue,"Phthalo Blue",#000f89,0,15,137
+phthalo_green,"Phthalo Green",#123524,18,53,36
+piggy_pink,"Piggy Pink",#fddde6,253,221,230
+pine_green,"Pine Green",#01796f,1,121,111
+pink,"Pink",#ffc0cb,255,192,203
+pink_lace,"Pink Lace",#ffddf4,255,221,244
+pink_orange,"Pink-Orange",#f96,255,153,102
+pink_pearl,"Pink Pearl",#e7accf,231,172,207
+pink_sherbet,"Pink Sherbet",#f78fa7,247,143,167
+pistachio,"Pistachio",#93c572,147,197,114
+platinum,"Platinum",#e5e4e2,229,228,226
+plum_traditional,"Plum (Traditional)",#8e4585,142,69,133
+plum_web,"Plum (Web)",#dda0dd,221,160,221
+portland_orange,"Portland Orange",#ff5a36,255,90,54
+powder_blue_web,"Powder Blue (Web)",#b0e0e6,176,224,230
+princeton_orange,"Princeton Orange",#ff8f00,255,143,0
+prune,"Prune",#701c1c,112,28,28
+prussian_blue,"Prussian Blue",#003153,0,49,83
+psychedelic_purple,"Psychedelic Purple",#df00ff,223,0,255
+puce,"Puce",#c89,204,136,153
+pumpkin,"Pumpkin",#ff7518,255,117,24
+purple_heart,"Purple Heart",#69359c,105,53,156
+purple_html_css,"Purple (Html/Css)",#800080,128,0,128
+purple_mountain_majesty,"Purple Mountain Majesty",#9678b6,150,120,182
+purple_munsell,"Purple (Munsell)",#9f00c5,159,0,197
+purple_pizzazz,"Purple Pizzazz",#fe4eda,254,78,218
+purple_taupe,"Purple Taupe",#50404d,80,64,77
+purple_x11,"Purple (X11)",#a020f0,160,32,240
+quartz,"Quartz",#51484f,81,72,79
+rackley,"Rackley",#5d8aa8,93,138,168
+radical_red,"Radical Red",#ff355e,255,53,94
+rajah,"Rajah",#fbab60,251,171,96
+raspberry,"Raspberry",#e30b5d,227,11,93
+raspberry_glace,"Raspberry Glace",#915f6d,145,95,109
+raspberry_pink,"Raspberry Pink",#e25098,226,80,152
+raspberry_rose,"Raspberry Rose",#b3446c,179,68,108
+raw_umber,"Raw Umber",#826644,130,102,68
+razzle_dazzle_rose,"Razzle Dazzle Rose",#f3c,255,51,204
+razzmatazz,"Razzmatazz",#e3256b,227,37,107
+red,"Red",#f00,255,0,0
+red_brown,"Red-Brown",#a52a2a,165,42,42
+red_devil,"Red Devil",#860111,134,1,17
+red_munsell,"Red (Munsell)",#f2003c,242,0,60
+red_ncs,"Red (Ncs)",#c40233,196,2,51
+red_orange,"Red-Orange",#ff5349,255,83,73
+red_pigment,"Red (Pigment)",#ed1c24,237,28,36
+red_ryb,"Red (Ryb)",#fe2712,254,39,18
+red_violet,"Red-Violet",#c71585,199,21,133
+redwood,"Redwood",#ab4e52,171,78,82
+regalia,"Regalia",#522d80,82,45,128
+resolution_blue,"Resolution Blue",#002387,0,35,135
+rich_black,"Rich Black",#004040,0,64,64
+rich_brilliant_lavender,"Rich Brilliant Lavender",#f1a7fe,241,167,254
+rich_carmine,"Rich Carmine",#d70040,215,0,64
+rich_electric_blue,"Rich Electric Blue",#0892d0,8,146,208
+rich_lavender,"Rich Lavender",#a76bcf,167,107,207
+rich_lilac,"Rich Lilac",#b666d2,182,102,210
+rich_maroon,"Rich Maroon",#b03060,176,48,96
+rifle_green,"Rifle Green",#414833,65,72,51
+robin_egg_blue,"Robin Egg Blue",#0cc,0,204,204
+rose,"Rose",#ff007f,255,0,127
+rose_bonbon,"Rose Bonbon",#f9429e,249,66,158
+rose_ebony,"Rose Ebony",#674846,103,72,70
+rose_gold,"Rose Gold",#b76e79,183,110,121
+rose_madder,"Rose Madder",#e32636,227,38,54
+rose_pink,"Rose Pink",#f6c,255,102,204
+rose_quartz,"Rose Quartz",#aa98a9,170,152,169
+rose_taupe,"Rose Taupe",#905d5d,144,93,93
+rose_vale,"Rose Vale",#ab4e52,171,78,82
+rosewood,"Rosewood",#65000b,101,0,11
+rosso_corsa,"Rosso Corsa",#d40000,212,0,0
+rosy_brown,"Rosy Brown",#bc8f8f,188,143,143
+royal_azure,"Royal Azure",#0038a8,0,56,168
+royal_blue_traditional,"Royal Blue (Traditional)",#002366,0,35,102
+royal_blue_web,"Royal Blue (Web)",#4169e1,65,105,225
+royal_fuchsia,"Royal Fuchsia",#ca2c92,202,44,146
+royal_purple,"Royal Purple",#7851a9,120,81,169
+royal_yellow,"Royal Yellow",#fada5e,250,218,94
+rubine_red,"Rubine Red",#d10056,209,0,86
+ruby,"Ruby",#e0115f,224,17,95
+ruby_red,"Ruby Red",#9b111e,155,17,30
+ruddy,"Ruddy",#ff0028,255,0,40
+ruddy_brown,"Ruddy Brown",#bb6528,187,101,40
+ruddy_pink,"Ruddy Pink",#e18e96,225,142,150
+rufous,"Rufous",#a81c07,168,28,7
+russet,"Russet",#80461b,128,70,27
+rust,"Rust",#b7410e,183,65,14
+rusty_red,"Rusty Red",#da2c43,218,44,67
+sacramento_state_green,"Sacramento State Green",#00563f,0,86,63
+saddle_brown,"Saddle Brown",#8b4513,139,69,19
+safety_orange_blaze_orange,"Safety Orange (Blaze Orange)",#ff6700,255,103,0
+saffron,"Saffron",#f4c430,244,196,48
+salmon,"Salmon",#ff8c69,255,140,105
+salmon_pink,"Salmon Pink",#ff91a4,255,145,164
+sand,"Sand",#c2b280,194,178,128
+sand_dune,"Sand Dune",#967117,150,113,23
+sandstorm,"Sandstorm",#ecd540,236,213,64
+sandy_brown,"Sandy Brown",#f4a460,244,164,96
+sandy_taupe,"Sandy Taupe",#967117,150,113,23
+sangria,"Sangria",#92000a,146,0,10
+sap_green,"Sap Green",#507d2a,80,125,42
+sapphire,"Sapphire",#0f52ba,15,82,186
+sapphire_blue,"Sapphire Blue",#0067a5,0,103,165
+satin_sheen_gold,"Satin Sheen Gold",#cba135,203,161,53
+scarlet,"Scarlet",#ff2400,255,36,0
+scarlet_crayola,"Scarlet (Crayola)",#fd0e35,253,14,53
+school_bus_yellow,"School Bus Yellow",#ffd800,255,216,0
+screamin_green,"Screamin' Green",#76ff7a,118,255,122
+sea_blue,"Sea Blue",#006994,0,105,148
+sea_green,"Sea Green",#2e8b57,46,139,87
+seal_brown,"Seal Brown",#321414,50,20,20
+seashell,"Seashell",#fff5ee,255,245,238
+selective_yellow,"Selective Yellow",#ffba00,255,186,0
+sepia,"Sepia",#704214,112,66,20
+shadow,"Shadow",#8a795d,138,121,93
+shamrock_green,"Shamrock Green",#009e60,0,158,96
+shocking_pink,"Shocking Pink",#fc0fc0,252,15,192
+shocking_pink_crayola,"Shocking Pink (Crayola)",#ff6fff,255,111,255
+sienna,"Sienna",#882d17,136,45,23
+silver,"Silver",#c0c0c0,192,192,192
+sinopia,"Sinopia",#cb410b,203,65,11
+skobeloff,"Skobeloff",#007474,0,116,116
+sky_blue,"Sky Blue",#87ceeb,135,206,235
+sky_magenta,"Sky Magenta",#cf71af,207,113,175
+slate_blue,"Slate Blue",#6a5acd,106,90,205
+slate_gray,"Slate Gray",#708090,112,128,144
+smalt_dark_powder_blue,"Smalt (Dark Powder Blue)",#039,0,51,153
+smokey_topaz,"Smokey Topaz",#933d41,147,61,65
+smoky_black,"Smoky Black",#100c08,16,12,8
+snow,"Snow",#fffafa,255,250,250
+spiro_disco_ball,"Spiro Disco Ball",#0fc0fc,15,192,252
+spring_bud,"Spring Bud",#a7fc00,167,252,0
+spring_green,"Spring Green",#00ff7f,0,255,127
+st_patrick_s_blue,"St. Patrick'S Blue",#23297a,35,41,122
+steel_blue,"Steel Blue",#4682b4,70,130,180
+stil_de_grain_yellow,"Stil De Grain Yellow",#fada5e,250,218,94
+stizza,"Stizza",#900,153,0,0
+stormcloud,"Stormcloud",#4f666a,79,102,106
+straw,"Straw",#e4d96f,228,217,111
+sunglow,"Sunglow",#fc3,255,204,51
+sunset,"Sunset",#fad6a5,250,214,165
+tan,"Tan",#d2b48c,210,180,140
+tangelo,"Tangelo",#f94d00,249,77,0
+tangerine,"Tangerine",#f28500,242,133,0
+tangerine_yellow,"Tangerine Yellow",#fc0,255,204,0
+tango_pink,"Tango Pink",#e4717a,228,113,122
+taupe,"Taupe",#483c32,72,60,50
+taupe_gray,"Taupe Gray",#8b8589,139,133,137
+tea_green,"Tea Green",#d0f0c0,208,240,192
+tea_rose_orange,"Tea Rose (Orange)",#f88379,248,131,121
+tea_rose_rose,"Tea Rose (Rose)",#f4c2c2,244,194,194
+teal,"Teal",#008080,0,128,128
+teal_blue,"Teal Blue",#367588,54,117,136
+teal_green,"Teal Green",#00827f,0,130,127
+telemagenta,"Telemagenta",#cf3476,207,52,118
+tenn_tawny,"Tenné (Tawny)",#cd5700,205,87,0
+terra_cotta,"Terra Cotta",#e2725b,226,114,91
+thistle,"Thistle",#d8bfd8,216,191,216
+thulian_pink,"Thulian Pink",#de6fa1,222,111,161
+tickle_me_pink,"Tickle Me Pink",#fc89ac,252,137,172
+tiffany_blue,"Tiffany Blue",#0abab5,10,186,181
+tiger_s_eye,"Tiger'S Eye",#e08d3c,224,141,60
+timberwolf,"Timberwolf",#dbd7d2,219,215,210
+titanium_yellow,"Titanium Yellow",#eee600,238,230,0
+tomato,"Tomato",#ff6347,255,99,71
+toolbox,"Toolbox",#746cc0,116,108,192
+topaz,"Topaz",#ffc87c,255,200,124
+tractor_red,"Tractor Red",#fd0e35,253,14,53
+trolley_grey,"Trolley Grey",#808080,128,128,128
+tropical_rain_forest,"Tropical Rain Forest",#00755e,0,117,94
+true_blue,"True Blue",#0073cf,0,115,207
+tufts_blue,"Tufts Blue",#417dc1,65,125,193
+tumbleweed,"Tumbleweed",#deaa88,222,170,136
+turkish_rose,"Turkish Rose",#b57281,181,114,129
+turquoise,"Turquoise",#30d5c8,48,213,200
+turquoise_blue,"Turquoise Blue",#00ffef,0,255,239
+turquoise_green,"Turquoise Green",#a0d6b4,160,214,180
+tuscan_red,"Tuscan Red",#7c4848,124,72,72
+twilight_lavender,"Twilight Lavender",#8a496b,138,73,107
+tyrian_purple,"Tyrian Purple",#66023c,102,2,60
+ua_blue,"Ua Blue",#03a,0,51,170
+ua_red,"Ua Red",#d9004c,217,0,76
+ube,"Ube",#8878c3,136,120,195
+ucla_blue,"Ucla Blue",#536895,83,104,149
+ucla_gold,"Ucla Gold",#ffb300,255,179,0
+ufo_green,"Ufo Green",#3cd070,60,208,112
+ultra_pink,"Ultra Pink",#ff6fff,255,111,255
+ultramarine,"Ultramarine",#120a8f,18,10,143
+ultramarine_blue,"Ultramarine Blue",#4166f5,65,102,245
+umber,"Umber",#635147,99,81,71
+unbleached_silk,"Unbleached Silk",#ffddca,255,221,202
+united_nations_blue,"United Nations Blue",#5b92e5,91,146,229
+university_of_california_gold,"University Of California Gold",#b78727,183,135,39
+unmellow_yellow,"Unmellow Yellow",#ff6,255,255,102
+up_forest_green,"Up Forest Green",#014421,1,68,33
+up_maroon,"Up Maroon",#7b1113,123,17,19
+upsdell_red,"Upsdell Red",#ae2029,174,32,41
+urobilin,"Urobilin",#e1ad21,225,173,33
+usafa_blue,"Usafa Blue",#004f98,0,79,152
+usc_cardinal,"Usc Cardinal",#900,153,0,0
+usc_gold,"Usc Gold",#fc0,255,204,0
+utah_crimson,"Utah Crimson",#d3003f,211,0,63
+vanilla,"Vanilla",#f3e5ab,243,229,171
+vegas_gold,"Vegas Gold",#c5b358,197,179,88
+venetian_red,"Venetian Red",#c80815,200,8,21
+verdigris,"Verdigris",#43b3ae,67,179,174
+vermilion_cinnabar,"Vermilion (Cinnabar)",#e34234,227,66,52
+vermilion_plochere,"Vermilion (Plochere)",#d9603b,217,96,59
+veronica,"Veronica",#a020f0,160,32,240
+violet,"Violet",#8f00ff,143,0,255
+violet_blue,"Violet-Blue",#324ab2,50,74,178
+violet_color_wheel,"Violet (Color Wheel)",#7f00ff,127,0,255
+violet_ryb,"Violet (Ryb)",#8601af,134,1,175
+violet_web,"Violet (Web)",#ee82ee,238,130,238
+viridian,"Viridian",#40826d,64,130,109
+vivid_auburn,"Vivid Auburn",#922724,146,39,36
+vivid_burgundy,"Vivid Burgundy",#9f1d35,159,29,53
+vivid_cerise,"Vivid Cerise",#da1d81,218,29,129
+vivid_tangerine,"Vivid Tangerine",#ffa089,255,160,137
+vivid_violet,"Vivid Violet",#9f00ff,159,0,255
+warm_black,"Warm Black",#004242,0,66,66
+waterspout,"Waterspout",#a4f4f9,164,244,249
+wenge,"Wenge",#645452,100,84,82
+wheat,"Wheat",#f5deb3,245,222,179
+white,"White",#fff,255,255,255
+white_smoke,"White Smoke",#f5f5f5,245,245,245
+wild_blue_yonder,"Wild Blue Yonder",#a2add0,162,173,208
+wild_strawberry,"Wild Strawberry",#ff43a4,255,67,164
+wild_watermelon,"Wild Watermelon",#fc6c85,252,108,133
+wine,"Wine",#722f37,114,47,55
+wine_dregs,"Wine Dregs",#673147,103,49,71
+wisteria,"Wisteria",#c9a0dc,201,160,220
+wood_brown,"Wood Brown",#c19a6b,193,154,107
+xanadu,"Xanadu",#738678,115,134,120
+yale_blue,"Yale Blue",#0f4d92,15,77,146
+yellow,"Yellow",#ff0,255,255,0
+yellow_green,"Yellow-Green",#9acd32,154,205,50
+yellow_munsell,"Yellow (Munsell)",#efcc00,239,204,0
+yellow_ncs,"Yellow (Ncs)",#ffd300,255,211,0
+yellow_orange,"Yellow Orange",#ffae42,255,174,66
+yellow_process,"Yellow (Process)",#ffef00,255,239,0
+yellow_ryb,"Yellow (Ryb)",#fefe33,254,254,51
+zaffre,"Zaffre",#0014a8,0,20,168
+zinnwaldite_brown,"Zinnwaldite Brown",#2c1608,44,22,8

requiremets.txt

@@ -0,0 +1,11 @@
+docopt==0.6.2
+numpy
+opencv-python
+pillow==6.1.0
+scipy==1.5.2 
+six==1.12.0  
+#torch==1.2.0 
+tqdm==4.49.0
+torch 
+torchvision 
+torchaudio

src/apps/classification.py

@@ -0,0 +1,88 @@
+import os
+import torch
+from PIL import Image
+import numpy as np
+from torch import cuda, device
+from torchvision import transforms
+from src.utils.utils import download_and_unzip_model
+
+class Classification:
+    def __init__(self, root_path, model_config):
+        self.root_path = root_path
+        self.model_config = model_config
+        self.model_name = f'{root_path}/{model_config["filename"]}'
+        self.image_size = model_config['image_size']
+        self.classes = model_config['classes']
+        self.filter_classes = model_config['filter_classes']
+        self.device = device("cuda:0" if cuda.is_available() else "cpu")
+        self.transform_image = self.transfrom_img()
+        self.model = self.__load_model()
+    
+    @staticmethod
+    def __check_model(root_path:str, model_config:dict) -> None:
+        if not os.path.isfile(f'{root_path}/{model_config["filename"]}'):
+            download_and_unzip_model(
+                root_dir    = root_path,
+                name        = model_config['filename'],
+                url         = model_config['url'],
+                file_size   = model_config['file_size'],
+                unzip       = False
+            )
+        else: print('Load model Classification')
+
+    def __load_model(self):
+        self.__check_model(self.root_path, self.model_config)
+        print(self.model_name)
+        return torch.load(self.model_name, map_location=self.device)
+        
+    def transfrom_img(self):
+        return transforms.Compose([
+            transforms.Resize(size=256),
+            transforms.CenterCrop(size=224),
+            transforms.ToTensor(),
+            ])
+    
+    @classmethod
+    def tensor_image_to_numpy(cls, tensor):
+        return tensor.detach().cpu().numpy() if tensor.requires_grad else tensor.cpu().numpy()
+    
+    def image_processing(self, image):
+        image = self.transform_image(image)
+        image = image.unsqueeze(0)
+        return image.to(self.device)
+    
+    def __call__(self, image):
+        if type(image) == np.ndarray:
+            image = Image.fromarray(image)
+        image = image.resize((self.image_size, self.image_size))
+        image = self.image_processing(image)
+        if torch.cuda.is_available():
+            image_tensor = image.view(1, 3, 224, 224).cuda()
+        else:
+            image_tensor = image.view(1, 3, 224, 224)
+        
+        with torch.no_grad():
+            output = self.model(image_tensor)
+        probs = torch.exp(output).to(self.device)
+        topk, topclass = probs.topk(len(self.filter_classes), dim=1)
+        result = list()
+        for i in range(len(probs[0])):
+            classes =  self.classes[topclass.cpu().numpy()[0][i]]
+            conf = round(topk.cpu().numpy()[0][i], 2)
+            if classes in self.filter_classes:
+                result.append([classes, conf])
+        return result
+
+if __name__ == '__main__':
+    root_path = os.path.expanduser('/Users/alimustofa/Downloads/')
+    classification_config = {
+        'filename'          : 'resnet34_model_400.pt',
+        'image_size'        : 480,
+        'classes'           :['almost_ripe', 'not_ripe', 'overripe', 'ripe'],
+        'filter_classes'    : ['almost_ripe', 'not_ripe', 'overripe', 'ripe'],
+        'url'               : 'https://github.com/Alimustoofaa/ContainerNumber-Dev/releases/download/detection_v1/container_iso_maxgross.pt',
+        'file_size'         : 14749585,
+    }
+
+    # model_name = '/Users/alimustofa/Downloads/resnet34_model_avorit.pt'
+    avori_classification = Classification(root_path,model_config=classification_config)

src/apps/detection.py

@@ -0,0 +1,197 @@
+'''
+@Author     : Ali Mustofa HALOTEC
+@Module     : Container Number Iso Code Detection
+@Created on : 10 Oct 2022
+'''
+#!/usr/bin/env python3
+# Path: src/apps/detection.py
+import os
+import cv2
+import numpy as np
+from PIL import Image
+from typing import Optional
+from pydantic import BaseModel
+from src.utils.utils import download_and_unzip_model
+
+import torch
+from torch import nn
+
+class InputDetection(BaseModel):
+	image: 			list
+	min_confidence: Optional[float] = 0.5
+	get_one: 		Optional[bool] 	= True
+	boxes_ori: 		Optional[bool] 	= True
+	resized_size: 	Optional[int] 	= 640
+	image_shape:	Optional[tuple] = (1280, 720, 3)
+	
+class Detection:
+	def __init__(self, root_path:str, model_config:dict) -> None:
+		'''
+		Load model 
+		@params:
+			- root_path:str ->  root of path model
+			- model_config:dict -> config of model {filename, classes, url, file_size}
+		'''
+		self.root_path :str          = root_path
+		self.model_config :dict      = model_config
+		self.model_name :str         = f'{root_path}/{model_config["filename"]}'
+		self.image_size :int         = model_config['image_size']
+		self.classes :list           = model_config['classes']
+		self.filter_classes :list    = model_config['filter_classes']
+		self.device :torch           = torch.device('cuda') if torch.cuda.is_available() else torch.device('cpu')
+		self.model :nn.Module        = self.__load_model()
+
+	@staticmethod
+	def __check_model(root_path:str, model_config:dict) -> None:
+		if not os.path.isfile(f'{root_path}/{model_config["filename"]}'):
+			download_and_unzip_model(
+				root_dir    = root_path,
+				name        = model_config['filename'],
+				url         = model_config['url'],
+				file_size   = model_config['file_size'],
+				unzip       = False
+			)
+		else: print('Load model char detection')
+
+	def __load_model(self) -> torch.nn.Module:
+		self.__check_model(self.root_path, self.model_config)
+		try:
+			model = torch.hub.load('ultralytics/yolov5', 'custom', path=self.model_name)
+		except:
+			model = torch.hub.load('ultralytics/yolov5', 'custom', path=self.model_name, force_reload=True)
+		return model
+	
+	def extract_results(self, results, min_confidence:float = 0.5, get_one=False, \
+		boxes_ori:bool = True, resized_size:int = 0, image_shape:tuple = (1080, 720)):
+		'''
+		Format result([tensor([[151.13147, 407.76913, 245.91382, 454.27802,   0.89075,   0.00000]])])
+		Filter min confidence prediction and classes id/name
+		Cropped image and get index max value confidence lavel
+		Args:
+			result(models.common.Detections): result detection YoloV5
+			min_confidence(float): minimal confidence detection in range 0-1
+			boxes_ori(bool): if true, calculate boxes to original resolution
+			resized_size(int): value of resized image detection
+			image_shape(tuple): height, width image original
+		Return:
+			result(dict): {
+				casess:[{
+					confidence(float): confidence,
+					bbox(list) : [x_min, y_min, x_max, y_max]
+				}]
+			}
+		'''
+		results_format  = results.xyxy
+		results_filter =  dict({i:list() for i in self.classes})
+		
+		if len(results_format[0]) >= 1:
+			for i in range(len(results_format[0])):
+				classes_name    = self.classes[int(results_format[0][i][-1])]
+				confidence      = float(results_format[0][i][-2])
+				if classes_name in self.filter_classes and confidence >= min_confidence:
+
+					x_min, y_min = int(results_format[0][i][0]), int(results_format[0][i][1])
+					x_max, y_max = int(results_format[0][i][2]), int(results_format[0][i][3])
+					# change coordinate to original w n h
+					if boxes_ori:
+						resized_size = self.image_size if resized_size == 0 else resized_size
+						height, width = image_shape[:2]
+						x_min = int((x_min/resized_size)*width)
+						y_min = int((y_min/resized_size)*height)
+						x_max = int((x_max/resized_size)*width)
+						y_max = int((y_max/resized_size)*height)
+
+					if get_one:
+						if results_filter[classes_name]:
+							if results_filter[classes_name][0]['confidence'] < confidence:
+								results_filter[classes_name][0] = \
+									{'confidence': round(confidence,2), 
+									'bbox':[x_min, y_min, x_max, y_max]}
+							# else: pass
+						else:
+							results_filter[classes_name].append({
+								'confidence': round(confidence,2), 
+								'bbox':[x_min, y_min, x_max, y_max]
+							})
+					else:
+						results_filter[classes_name].append({
+							'confidence': round(confidence,2), 
+							'bbox':[x_min, y_min, x_max, y_max]
+						})
+		# Delete key if detection null
+		for i in self.classes:results_filter.__delitem__(i) if not results_filter[i] else None
+
+		return results_filter
+	
+	@staticmethod
+	def visualize_result(image:np.array, results_filter:dict) -> np.array:
+		'''
+		Draw bounding box result
+		Args:
+			image(numpy.ndarray) : image/frame
+			results_filter(dict) : {
+				casess:[{
+					confidence(float): confidence,
+					bbox(list) : [x_min, y_min, x_max, y_max]
+				}]
+			}
+		Return:
+			image(numpy.ndarray) : image drawed
+		'''
+		for result in results_filter.items():
+			label = result[0]
+			for i in result[1]:
+				conf = int(i['confidence']*100)
+				bbox = i['bbox']
+				x_min, y_min, x_max, y_max = \
+				bbox[0], bbox[1], bbox[2], bbox[3]
+
+				cv2.rectangle(image, (x_min, y_min), (x_max, y_max), (86, 71, 255), 2)
+				# Draw text
+				label_conf = f'{label.upper()}:{conf}%'
+				cv2.rectangle(image, (x_min, y_min-20), (x_min+(len(label_conf)*13), y_min), (86, 71, 255), cv2.FILLED)
+				cv2.putText(image, label_conf, (x_min, y_min), cv2.FONT_HERSHEY_SIMPLEX, 0.7, (255, 255, 255), 2)
+		return image
+
+	def __call__(self, image:np.array, size:int = None):
+		'''
+		Prediction image object detectionn YoloV5
+		Args:
+			image(numpy.ndarray) : image/frame
+		Return:
+			results_prediction(models.common.Detections) : results -> convert to (results.xyxy/resultsxywh)
+		'''
+		if size: results = self.model(image, size=size)
+		else: results = self.model(image)
+		return results
+
+if __name__ == '__main__':
+	root_path = os.path.expanduser('/Users/alimustofa/Downloads/')
+	detection_config = {
+		'filename'          : 'avori_detection.pt',
+		'image_size'        : 640,
+		'classes'           : ['avocado'],
+		'filter_classes'    : ['avocado'],
+		'url'               : 'https://github.com/Alimustoofaa/ContainerNumber-Dev/releases/download/detection_v1/container_iso_maxgross.pt',
+		'file_size'         : 14749585,
+		
+	}
+	detection = Detection(root_path, detection_config)
+
+	image = cv2.imread('12022051823052897.jpg')
+	image_resize = cv2.resize(
+					image.copy(),
+					(detection_config['image_size'], 
+					detection_config['image_size']), 
+					interpolation = cv2.INTER_AREA)
+
+	results = detection(image_resize, size=detection_config['image_size'])
+	filtered = detection.extract_results(
+					results, 0.5,
+					get_one=True, 
+					boxes_ori=True, 
+					resized_size=detection_config['image_size'], 
+					image_shape=image.shape)
+	img_drawed = detection.visualize_result(image.copy(), filtered)
+	cv2.imwrite('img_drawed.jpg', img_drawed)
+	Image.fromarray(cv2.cvtColor(img_drawed, cv2.COLOR_BGR2RGB))

src/configs/models.py

@@ -0,0 +1,26 @@
+import os
+
+ROOT_PATH = os.path.expanduser('/Users/alimustofa/Downloads')
+
+DETECTION_CONFIG = {
+    'avocado': {
+        'filename'          : 'avori_detection.pt',
+        'image_size'        : 640,
+        'classes'           : ['avocado'],
+        'filter_classes'    : ['avocado'],
+        'url'               : 'https://github.com/Alimustoofaa/ContainerNumber-Dev/releases/download/detection_v1/container_iso_maxgross.pt',
+        'file_size'         : 14749585,
+    }
+}
+
+CLASSIFICATION_CONFIG = {
+    'avocado': {
+        'filename'          : 'resnet34_model_avorit.pt',
+        'image_size'        : 480,
+        'classes'           :['almost_ripe', 'not_ripe', 'overripe', 'ripe'],
+        'filter_classes'    : ['almost_ripe', 'not_ripe', 'overripe', 'ripe'],
+        'url'               : 'https://github.com/Alimustoofaa/ContainerNumber-Dev/releases/download/detection_v1/container_iso_maxgross.pt',
+        'file_size'         : 14749585,
+    }
+}
+

src/models.py

@@ -0,0 +1,26 @@
+import os
+
+ROOT_PATH = os.path.expanduser('/Users/alimustofa/Downloads')
+
+DETECTION_CONFIG = {
+    'avocado': {
+        'filename'          : 'avori_detection.pt',
+        'image_size'        : 640,
+        'classes'           : ['avocado'],
+        'filter_classes'    : ['avocado'],
+        'url'               : 'https://github.com/Alimustoofaa/ContainerNumber-Dev/releases/download/detection_v1/container_iso_maxgross.pt',
+        'file_size'         : 14749585,
+    }
+}
+
+CLASSIFICATION_CONFIG = {
+    'avocado': {
+        'filename'          : 'resnet34_model_avorit.pt',
+        'image_size'        : 480,
+        'classes'           :['almost_ripe', 'not_ripe', 'overripe', 'ripe'],
+        'filter_classes'    : ['almost_ripe', 'not_ripe', 'overripe', 'ripe'],
+        'url'               : 'https://github.com/Alimustoofaa/ContainerNumber-Dev/releases/download/detection_v1/container_iso_maxgross.pt',
+        'file_size'         : 14749585,
+    }
+}
+

src/process.py

@@ -0,0 +1,101 @@
+import cv2
+import numpy as np
+from .apps.detection import Detection
+from .apps.classification import Classification
+
+from .configs.models import *
+from .utils.colors import recognize_color
+
+from typing import List
+from typing import Optional
+from pydantic import BaseModel
+
+detection_config = DETECTION_CONFIG['avocado']
+classification_config = CLASSIFICATION_CONFIG['avocado']
+detection       = Detection(ROOT_PATH, detection_config)
+classification  = Classification(ROOT_PATH, classification_config)
+
+
+def get_avg_color(image):
+    img_temp = image.copy()
+    img_temp[:,:,0], img_temp[:,:,1], img_temp[:,:,2] = np.average(image, axis=(0,1))
+    img_temp = cv2.resize(img_temp, (25,25))
+    return img_temp
+
+def get_texture_image(image):
+    h, w = image.shape[:2]
+    # Calculate centroid
+    cx, cy= int(w/2), int(h/2)
+    # radius crop
+    radius_cx , radius_cy = int(0.5*cx), int(0.5*cy)
+    x_min, y_min, x_max, y_max = cx-radius_cx, cy-radius_cy, cx+radius_cx, cy+radius_cy
+    return image[y_min:y_max, x_min:x_max]
+
+def image_classification(image):
+    results = list()
+    image_resize = cv2.resize(
+                image.copy(),
+                (classification_config['image_size'], 
+                classification_config['image_size']), 
+                interpolation = cv2.INTER_AREA)
+    results_class = classification(image_resize)
+    for i in results_class:
+        results.append([i[0], int(i[1]*100)])
+        print(f'Classification : {i[0]} | confidecne : {int(i[1]* 100)} %')
+    return results
+
+class Detection(BaseModel):
+    label : str
+    conf  : float
+    bbox  : list
+
+class ResultFruit(BaseModel):
+    detection	: Optional[Detection] = {}
+    classification_texture: Optional[list] = []
+    classification_color: Optional[str] = ''
+
+
+def main_process(image):
+    # results_fruit = {
+    #     'detection': None,
+    #     'classification_texture': list(),
+    #     'classification_color': None
+    # }
+    image_resize = cv2.resize(
+                image.copy(),
+                (detection_config['image_size'], 
+                detection_config['image_size']), 
+                interpolation = cv2.INTER_AREA)
+    cv2.imwrite('image.jpg', image)
+    # Detection
+    results = detection(image_resize, size=detection_config['image_size'])
+    result_detection = detection.extract_results(
+                results, 0.0,
+                get_one=True, 
+                boxes_ori=True, 
+                resized_size=detection_config['image_size'])
+    print(result_detection)
+    # results['detection'] = result_detection
+    try:
+        confidence_c = result_detection['avocado'][0]['confidence']
+        x_min_a, y_min_a, x_max_a, y_max_a = result_detection['avocado'][0]['bbox']
+        img_avocade = image[y_min_a:y_max_a, x_min_a:x_max_a]
+        # get texture image 
+        img_texture = get_texture_image(img_avocade)
+        # classification
+        result_classification = image_classification(img_texture)
+        # Color classification
+        avg_color = get_avg_color(img_texture)
+        b,g,r = avg_color[1,1]
+        b,g,r =int(b),int(g),int(r) 
+        result_color = recognize_color(b,g,r)
+        result_fruit = ResultFruit(
+            detection= {'label': 'avocado', 'conf': int(confidence_c*100), 'bbox': [x_min_a, y_min_a, x_max_a, y_max_a]},
+            classification_texture = result_classification,
+            classification_color = result_color
+        )
+    except KeyError:
+        result_fruit = ResultFruit()
+    # print(result_fruit.json())
+    # print(type(result_fruit.json()))
+    return result_fruit

src/process_gradio.py

@@ -0,0 +1,88 @@
+import cv2
+import numpy as np
+from .apps.detection import Detection
+from .apps.classification import Classification
+
+from .configs.models import *
+from .utils.colors import recognize_color
+
+detection_config = DETECTION_CONFIG['avocado']
+classification_config = CLASSIFICATION_CONFIG['avocado']
+detection       = Detection(ROOT_PATH, detection_config)
+classification  = Classification(ROOT_PATH, classification_config)
+
+
+def get_avg_color(image):
+    img_temp = image.copy()
+    img_temp[:,:,0], img_temp[:,:,1], img_temp[:,:,2] = np.average(image, axis=(0,1))
+    img_temp = cv2.resize(img_temp, (25,25))
+    return img_temp
+
+def get_texture_image(image):
+    h, w = image.shape[:2]
+    # Calculate centroid
+    cx, cy= int(w/2), int(h/2)
+    # radius crop
+    radius_cx , radius_cy = int(0.5*cx), int(0.5*cy)
+    x_min, y_min, x_max, y_max = cx-radius_cx, cy-radius_cy, cx+radius_cx, cy+radius_cy
+    return image[y_min:y_max, x_min:x_max]
+
+def image_classification(image):
+    results_conf = list()
+    results_class = list()
+    image_resize = cv2.resize(
+                image.copy(),
+                (classification_config['image_size'], 
+                classification_config['image_size']), 
+                interpolation = cv2.INTER_AREA)
+    results_classification = classification(image_resize)
+    for i in results_classification:
+        results_conf.append(i[1])
+        results_class.append(i[0])
+        print(f'Classification : {i[0]} | confidecne : {i[1]} %')
+    return results_class, results_conf
+
+
+def main_process(image):
+    image_resize = cv2.resize(
+                image.copy(),
+                (detection_config['image_size'], 
+                detection_config['image_size']), 
+                interpolation = cv2.INTER_AREA)
+    # Detection
+    results = detection(image_resize, size=detection_config['image_size'])
+    result_detection = detection.extract_results(
+                results, 0.0,
+                get_one=True, 
+                boxes_ori=True, 
+                resized_size=detection_config['image_size'],
+                image_shape=image.shape)
+    image_drawed = detection.visualize_result(
+        image.copy(), result_detection
+    )
+
+    # results['detection'] = result_detection
+    try:
+        confidence_c = result_detection['avocado'][0]['confidence']
+        x_min_a, y_min_a, x_max_a, y_max_a = result_detection['avocado'][0]['bbox']
+        img_avocade = image[y_min_a:y_max_a, x_min_a:x_max_a]
+        # get texture image 
+        img_texture = get_texture_image(img_avocade)
+        # classification
+        results_class, results_conf = image_classification(img_texture)
+        # Color classification
+        avg_color = get_avg_color(img_texture)
+        b,g,r = avg_color[1,1]
+        b,g,r =int(b),int(g),int(r) 
+        result_color = recognize_color(b,g,r)
+        # result_fruit = ResultFruit(
+        #     detection= {'label': 'avocado', 'conf': int(confidence_c*100), 'bbox': [x_min_a, y_min_a, x_max_a, y_max_a]},
+        #     classification_texture = result_classification,
+        #     classification_color = result_color
+        # )
+    except KeyError:
+        return image, dict(zip(classification_config['filter_classes'], map(float, [0,0,0,0])))
+    # print(result_fruit.json())
+    # print(type(result_fruit.json()))
+    print(dict(zip(results_class, map(float, results_conf))))
+    return image_drawed, dict(zip(results_class, map(float, results_conf)))

src/utils/colors.py

@@ -0,0 +1,18 @@
+# COLOR Data
+
+import pandas as pd
+
+index=["color", "color_name", "hex", "R", "G", "B"]
+csv = pd.read_csv('colors.csv', names=index, header=None)
+def recognize_color(R,G,B):
+    minimum = 10000
+    for i in range(len(csv)):
+        d = abs(R- int(csv.loc[i,"R"])) + abs(G- int(csv.loc[i,"G"]))+ abs(B- int(csv.loc[i,"B"]))
+        if(d<=minimum):
+            minimum = d
+            cname = csv.loc[i,"color_name"]
+    return cname
+
+# b,g,r = img_avg_color[1,1]
+# b,g,r =int(b),int(g),int(r) 
+# recognize_color(b,g,r)

src/utils/utils.py

@@ -0,0 +1,73 @@
+import os
+import cv2
+import base64
+import requests
+import numpy as np
+from tqdm import tqdm
+from pathlib import Path
+from zipfile import ZipFile
+
+def download_and_unzip_model(root_dir:str, name:str, 
+    url:str, file_size:int, unzip:bool = False):
+	'''
+	Checking model in model_path
+	download model if file not found
+	@params:
+ 		root_dir(str): The root directory of model.
+		name(str): The name of model.
+		url(str): The url of model.
+		file_size(int): The size of model.
+		unzip(bool): Unzip the model or not.
+	'''
+	Path(root_dir).mkdir(parents=True, exist_ok=True)
+
+	# check if model is already or not
+	print(f'Downloading {root_dir.split("/")[-1]} model, please wait.')
+	response = requests.get(url, stream=True)
+	
+	progress = tqdm(response.iter_content(1024), 
+				f'Downloading model', 
+				total=file_size, unit='B', 
+				unit_scale=True, unit_divisor=1024)
+	save_dir = f'{root_dir}/{name}'
+	with open(save_dir, 'wb') as f:
+		for data in progress:
+			f.write(data)
+			progress.update(len(data))
+		print(f'Done downloading  {root_dir.split("/")[-1]} model.')
+
+	# unzip model
+	if unzip:
+		with ZipFile(save_dir, 'r') as zip_obj:
+			zip_obj.extractall(root_dir)
+			print(f'Done unzip {root_dir.split("/")[-1]} model.')
+		os.remove(save_dir)
+
+def encode_image2string(image):
+	image_list = cv2.imencode('.jpg', image)[1]
+	image_bytes = image_list.tobytes()
+	image_encoded = base64.b64encode(image_bytes)
+	return image_encoded
+
+def decode_string2image(image_encoded):
+	jpg_original = base64.b64decode(image_encoded)
+	jpg_as_np = np.frombuffer(jpg_original, dtype=np.uint8)
+	image = cv2.imdecode(jpg_as_np, flags=1)
+	return image
+
+def resize_image(image, size_percent):
+    '''
+    Resize an image so that its longest edge equals to the given size.
+    Args:
+        image(cv2.Image): The input image.
+        size_percent(int): The size of longest edge.
+    Returns:
+        image(cv2.Image): The output image.
+    '''
+    width   = int(image.shape[1] * size_percent / 100)
+    height  = int(image.shape[0] * size_percent / 100)
+    dim     = (width, height)
+    
+    # resize image
+    resized = cv2.resize(image, dim, interpolation = cv2.INTER_AREA)
+    return resized