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ac6ed41 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 | import cv2
import numpy as np
import gradio as gr
from inference_sdk import InferenceHTTPClient
from PIL import Image
# Initialize API client
CLIENT = InferenceHTTPClient(
api_url="https://outline.roboflow.com",
api_key="yu2FwTnkRok26cNiMo8e"
)
# Predefined color options
color_options = {
"🔴 Red": (0, 0, 255),
"🔵 Blue": (255, 0, 0),
"🟢 Green": (0, 255, 0),
"💖 Pink": (203, 192, 255),
"💜 Purple": (128, 0, 128),
"⚫ Black": (0, 0, 0),
"⚪ White": (255, 255, 255)
}
# Function to apply nail paint
def apply_nail_paint(image, selected_color):
image = np.array(image)
image = cv2.cvtColor(image, cv2.COLOR_RGB2BGR)
result = CLIENT.infer(image, model_id="seg_nail_test/1")
mask = np.zeros(image.shape[:2], dtype=np.uint8)
for pred in result['predictions']:
if 'points' in pred:
points = np.array([[p['x'], p['y']] for p in pred['points']], dtype=np.int32)
cv2.fillPoly(mask, [points], 255)
mask = cv2.GaussianBlur(mask, (7, 7), 5)
mask = cv2.erode(mask, None, iterations=1)
mask = cv2.dilate(mask, None, iterations=2)
mask_3d = cv2.cvtColor(mask, cv2.COLOR_GRAY2BGR)
color_bgr = color_options[selected_color]
color_nails = np.full_like(image, color_bgr, dtype=np.uint8)
colored_nails = cv2.addWeighted(image, 0.4, color_nails, 0.6, 0)
final_nails = np.where(mask_3d == 255, colored_nails, image)
glossy_nails = cv2.addWeighted(final_nails, 0.9, mask_3d, 0.1, 0)
glossy_nails = cv2.cvtColor(glossy_nails, cv2.COLOR_BGR2RGB)
return Image.fromarray(glossy_nails)
# Function to apply nail texture
def apply_nail_texture(image, texture):
image = np.array(image)
texture = np.array(texture)
result = CLIENT.infer(image, model_id="seg_nail_test/1")
mask = np.zeros(image.shape[:2], dtype=np.uint8)
for pred in result['predictions']:
if 'points' in pred:
points = np.array([[p['x'], p['y']] for p in pred['points']], dtype=np.int32)
cv2.fillPoly(mask, [points], 255)
mask = cv2.GaussianBlur(mask, (7, 7), 5)
mask = cv2.erode(mask, None, iterations=1)
mask = cv2.dilate(mask, None, iterations=2)
mask_3d = cv2.cvtColor(mask, cv2.COLOR_GRAY2BGR)
texture_resized = cv2.resize(texture, (image.shape[1], image.shape[0]))
textured_nails = np.where(mask_3d == 255, texture_resized, image)
# textured_nails = cv2.cvtColor(textured_nails, cv2.COLOR_BGR2RGB)
return Image.fromarray(textured_nails)
# Function to handle dropdown selection
def process_image(mode, image, selected_color=None, texture=None):
if mode == "Apply Paint":
return apply_nail_paint(image, selected_color)
elif mode == "Apply Texture":
return apply_nail_texture(image, texture)
# Function to clear all inputs/outputs
def clear_inputs():
return None, None, None, None
# Gradio UI
with gr.Blocks() as demo:
gr.Markdown("## Nail Paint & Texture Application")
mode = gr.Dropdown(
["Apply Paint", "Apply Texture"],
label="Select Mode",
value="Apply Paint"
)
with gr.Row():
image_input = gr.Image(type="pil", label="Upload Hand Image")
color_input = gr.Radio(choices=list(color_options.keys()), label="Select Nail Color", visible=True)
texture_input = gr.Image(type="pil", label="Upload Texture Image", visible=False)
output_image = gr.Image(type="pil", label="Output Image")
def update_inputs(selected_mode):
if selected_mode == "Apply Paint":
return gr.update(visible=True), gr.update(visible=False)
else:
return gr.update(visible=False), gr.update(visible=True)
mode.change(update_inputs, inputs=[mode], outputs=[color_input, texture_input])
with gr.Row():
process_btn = gr.Button("Process")
clear_btn = gr.Button("Clear")
process_btn.click(process_image, inputs=[mode, image_input, color_input, texture_input], outputs=output_image)
clear_btn.click(clear_inputs, outputs=[image_input, color_input, texture_input, output_image])
demo.launch()
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