Найти подграф из Dashboard в Python ⇐ Python

[Anonymous]

Я хочу обнаружить подграфы на панели мониторинга. Я попробовал несколько способов. Мой код обнаруживает 85% подграфов на информационной панели, например
1.рабочая панель
2.работает
но для панели мониторинга ниже
3.Панель мониторинга не работает
Столкнулась с проблемой обнаружения, поскольку не может обнаружить прямоугольники из-за текста
найдите ниже код, который я использую, или предложите другой способ извлечения подграфов из панели управления
import cv2
from pathlib import Path

def extract_graphs(image_path, output_dir):
image = cv2.imread(image_path)
if image is None:
raise ValueError("Could not read the image")

# Convert to grayscale
gray = cv2.cvtColor(image, cv2.COLOR_BGR2GRAY)

# Apply threshold to get binary image
_, binary = cv2.threshold(gray, 240, 255, cv2.THRESH_BINARY_INV)

# Find contours
img_countours = image.copy()
contours, hierarchy = cv2.findContours(binary, cv2.RETR_EXTERNAL, cv2.CHAIN_APPROX_SIMPLE)
image_with_contours = cv2.drawContours(img_countours, contours, -1, (0, 255, 0), 1)

Path(output_dir).mkdir(parents=True, exist_ok=True)

# Minimum area threshold to filter out noise
min_area = 1000

# Aspect ratio thresholds (you can adjust these based on your needs)
min_width = 30 # Minimum acceptable width
min_height = 30 # Minimum acceptable height
max_aspect_ratio = 3 # Maximum width-to-height ratio for a proper rectangle/square
min_aspect_ratio = 0.4 # Minimum acceptable width-to-height ratio (to prevent too narrow graphs)

# Process each contour
for idx, contour in enumerate(contours):
# Calculate contour area
area = cv2.contourArea(contour)
if area > min_area:
# Get bounding rectangle
x, y, w, h = cv2.boundingRect(contour)

# Reject graphs that are too narrow or too small
if w < min_width or h < min_height:
continue

# Check the aspect ratio (width / height) to ensure it's a proper rectangle
aspect_ratio = w / h if h != 0 else 0
if aspect_ratio < min_aspect_ratio or aspect_ratio > max_aspect_ratio:
continue

# Add padding around the graph (optional)
padding = 10
x = max(0, x - padding)
y = max(0, y - padding)
w = min(image.shape[1] - x, w + 2 * padding)
h = min(image.shape[0] - y, h + 2 * padding)

# Extract the graph region
graph = image[y:y+h, x:x+w]

# Save the extracted graph
output_path = f"{output_dir}/graph_{idx}.png"
cv2.imwrite(output_path, graph)
print(f"Saved graph {idx} to {output_path}")

# image_path = "img/Retail_Sales_Distribution_Network_Dashboard_With_Forecasting_3 (1).jpg"
image_path = "img/Predictive_Modeling_Model_Performance_1.jpg"
#image_path = "img/Revenue_Dashboard_2.jpg"
output_dir = "out"

extract_graphs(image_path, output_dir)



Подробнее здесь: https://stackoverflow.com/questions/791 ... -in-python