Create app.py

app.py

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+import gradio as gr
+import torch
+import cv2
+import numpy as np
+import pytesseract
+from PIL import Image
+
+# YOLOv5 modelini yükle (örnek: yolov5s)
+model = torch.hub.load('ultralytics/yolov5', 'custom', path='yolov5s.pt', force_reload=True)
+
+def detect_and_ocr(image):
+    # YOLOv5 ile plaka tespiti
+    results = model(image)
+    labels, cords = results.xyxyn[0][:, -1], results.xyxyn[0][:, :-1]
+    img = np.array(image)
+    h, w, _ = img.shape
+    plates = []
+    for i, (label, cord) in enumerate(zip(labels, cords)):
+        if int(label) == 0:  # 0: 'license-plate' olarak eğitilmişse
+            x1, y1, x2, y2, conf = cord
+            x1, y1, x2, y2 = int(x1*w), int(y1*h), int(x2*w), int(y2*h)
+            plate_img = img[y1:y2, x1:x2]
+            plates.append(plate_img)
+    if not plates:
+        return "Plaka bulunamadı."
+    # OCR
+    ocr_results = []
+    for plate in plates:
+        text = pytesseract.image_to_string(plate, config='--psm 7')
+        ocr_results.append(text.strip())
+    return "\n".join(ocr_results)
+
+iface = gr.Interface(
+    fn=detect_and_ocr,
+    inputs=gr.Image(source="upload", tool="editor", type="pil", label="Fotoğraf yükle veya çek"),
+    outputs="text",
+    title="Araç Plaka Tanıma ve OCR",
+    description="Kamera ile fotoğraf çek veya yükle, plaka ve yazı otomatik tespit edilsin."
+)
+
+iface.launch()