Update app.py

app.py

@@ -1,8 +1,9 @@
 try:
+    import cloudinary
     import detectron2
 except:
     import os 
-    os.system('pip install git+https://github.com/facebookresearch/detectron2.git')
+    os.system('pip install cloudinary')
 
 import cv2
 import json
@@ -32,6 +33,23 @@ from detectron2.engine import DefaultPredictor
 from detectron2.config import get_cfg
 from detectron2.utils.visualizer import Visualizer
 from detectron2.data import MetadataCatalog, DatasetCatalog
+
+
+
+import cloudinary.uploader
+import io
+import os
+API_KEY =os.environ.getattribute("API_KEY")
+Cloud_Name =os.environ.getattribute("Cloud_Name")
+API_Secret =os.environ.getattribute("API_Secret")
+
+# Print the Cloudinary URL of the uploaded file
+print(upload_result["url"])
+
+
+
+
+
 # try:
 #     register_coco_instances("Fiber", {}, "./labels-fiver.json", "./Fiber")
 #     Fiber_metadata = MetadataCatalog.get("Fiber")
@@ -135,16 +153,37 @@ def inference(image_url, image, min_score):
         segmentation = np.where(item_mask == True)
         measurement = int(0.5+len(segmentation[0])/600)
         measurements[ind] = {'measurement': measurement, 'x_min': x_min, 'x_max': x_max, 'y_min': y_min, 'y_max': y_max}
+    cloudinary.config(
+      cloud_name = Cloud_Name,
+      api_key = API_KEY,
+      api_secret = API_Secret,
+      secure = True
+    )
+    
+    # Replace with the name of your CSV file
+    filename = "your_file.csv"
     
+    
+
+
     # Write the measurements to a CSV file
     with open('dmeasurements.csv', mode='w') as file:
         writer = csv.writer(file)
         writer.writerow(['ID', 'Measurement', 'X_Min', 'X_Max', 'Y_Min', 'Y_Max'])
         for id, data in measurements.items():
             writer.writerow([id, data['measurement'], data['x_min'], data['x_max'], data['y_min'], data['y_max']])
+            # Convert the CSV content to a bytes object
+        csv_bytes = io.StringIO( file).read().encode("utf-8")
+        
+        # Upload the file to Cloudinary
+        upload_result = cloudinary.uploader.upload(
+            csv_bytes,
+            resource_type = "raw",
+            folder = "csv_files"
+        )
         # return file
 
-    return "dmeasurements.csv"
+    return upload_result["url"]
 
 
 title = " Detectron2 Model Demo"