Spaces:
Runtime error
Runtime error
File size: 2,513 Bytes
5d670ae da9f292 5d670ae da9f292 61b752b 5d670ae da9f292 363a646 65ed4c1 363a646 da9f292 61b752b ddf8948 61b752b ddf8948 3ca006e ddf8948 ee1d691 ddf8948 61b752b ddf8948 61b752b ddf8948 61b752b ddf8948 477d4fe ddf8948 61b752b ddf8948 61b752b ddf8948 acddb2f 103f82b 61b752b ddf8948 61b752b ddf8948 61b752b ddf8948 103f82b ddf8948 8fe1b94 65ed4c1 2132698 |
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 |
import easyocr
import numpy as np
import cv2
import re
# Load EasyOCR reader
reader = easyocr.Reader(['en'], gpu=False)
def extract_weight_from_image(pil_img):
try:
img = np.array(pil_img)
# Resize very large images
max_dim = 1000
height, width = img.shape[:2]
if max(height, width) > max_dim:
scale = max_dim / max(height, width)
img = cv2.resize(img, None, fx=scale, fy=scale, interpolation=cv2.INTER_AREA)
# OCR recognition
results = reader.readtext(img)
print("DEBUG OCR RESULTS:", results)
raw_texts = []
weight_candidates = []
fallback_weight = None
fallback_conf = 0.0
for _, (text, conf) in results:
original = text
cleaned = text.lower().strip()
# Fix common OCR misreads
cleaned = cleaned.replace(",", ".")
cleaned = cleaned.replace("o", "0").replace("O", "0")
cleaned = cleaned.replace("s", "5").replace("S", "5")
cleaned = cleaned.replace("g", "9").replace("G", "6")
cleaned = cleaned.replace("kg", "").replace("kgs", "")
cleaned = re.sub(r"[^0-9\.]", "", cleaned)
raw_texts.append(f"{original} → {cleaned} (conf: {round(conf, 2)})")
# Save fallback if no match later
if cleaned and cleaned.replace(".", "").isdigit() and not fallback_weight:
fallback_weight = cleaned
fallback_conf = conf
# Match proper weight format: 75.02, 97.2, 105
if cleaned.count(".") <= 1 and re.fullmatch(r"\d{2,4}(\.\d{1,3})?", cleaned):
weight_candidates.append((cleaned, conf))
# Choose best candidate
if weight_candidates:
best_weight, best_conf = sorted(weight_candidates, key=lambda x: -x[1])[0]
elif fallback_weight:
best_weight, best_conf = fallback_weight, fallback_conf
else:
return "Not detected", 0.0, "\n".join(raw_texts)
# Strip unnecessary leading zeros
if "." in best_weight:
int_part, dec_part = best_weight.split(".")
int_part = int_part.lstrip("0") or "0"
best_weight = f"{int_part}.{dec_part}"
else:
best_weight = best_weight.lstrip("0") or "0"
return best_weight, round(best_conf * 100, 2), "\n".join(raw_texts)
except Exception as e:
return f"Error: {str(e)}", 0.0, "OCR failed"
|