resolved the filename issue in which filename cannot have dot

app.py

@@ -224,6 +224,8 @@ def perform_inference(file_paths: Dict[str, str]):
                 # upload the document to s3 bucket here
 
 
+                print("this is folder name",folder_name)
+
                 response = client.upload_file(local_file_path,bucket_name,folder_name,file_name)
 
                 print("The file has been uploaded to s3 bucket",response)
@@ -265,54 +267,61 @@ async def aadhar_ocr(
     cheque_file: UploadFile = File(None),
     gst_file: UploadFile = File(None),
 ):
-    try:
+    # try:
         # Handle file uploads
-        file_paths = {}
-        for file_type, folder in UPLOAD_DIRS.items():
-            file = locals()[file_type]  # Dynamically access the file arguments
-            if file:
-                # Save the file in the respective directory
-                file_path = os.path.join(folder, file.filename)
-                with open(file_path, "wb") as buffer:
-                    shutil.copyfileobj(file.file, buffer)
-                file_paths[file_type] = file_path
-
-        # Log received files
-        logging.info(f"Received files: {list(file_paths.keys())}")
-        print("file_paths",file_paths)
-        
-        files = {}
-        for key, value in file_paths.items():
-            name = value.split("/")[-1].split(".")[0]
-            id_type = key.split("_")[0]
-            doc_type = value.split("/")[-1].split(".")[1]
-            f_path = value
-            preprocessing = doc_processing(name,id_type,doc_type,f_path)
-            response = preprocessing.process()
-            files[key] = response["output_p"] + "&&" + f_path
-            # files["unprocessed_file_path"] = f_path
-            print("response",response)
+    file_paths = {}
+    for file_type, folder in UPLOAD_DIRS.items():
+        file = locals()[file_type]  # Dynamically access the file arguments
+        if file:
+            # Save the file in the respective directory
+            file_path = os.path.join(folder, file.filename)
+
+            print("this is the filename",file.filename)
+            with open(file_path, "wb") as buffer:
+                shutil.copyfileobj(file.file, buffer)
+            file_paths[file_type] = file_path
+
+    # Log received files
+    logging.info(f"Received files: {list(file_paths.keys())}")
+    print("file_paths",file_paths)
+    
+    files = {}
+    for key, value in file_paths.items():
+        name = value.split("/")[-1].split(".")[0]
+        id_type = key.split("_")[0]
+        doc_type = value.split("/")[-1].split(".")[-1]
+        f_path = value
 
-        
-        # Perform inference
-        result = perform_inference(files)
+        print("variables required",name,id_type,doc_type,f_path)
+        preprocessing = doc_processing(name,id_type,doc_type,f_path)
+        response = preprocessing.process()
+
+        print("response after preprocessing",response)
+
+        files[key] = response["output_p"] + "&&" + f_path
+        # files["unprocessed_file_path"] = f_path
+        print("response",response)
 
-        print("this is the result we got",result)
-        if "status" in list(result.keys()):
-            raise Exception("Custom error message")
-        # if result["status"] == "error":
-            
+    
+    # Perform inference
+    result = perform_inference(files)
 
+    print("this is the result we got",result)
+    if "status" in list(result.keys()):
+        raise Exception("Custom error message")
+    # if result["status"] == "error":
+        
 
-        return {"status": "success", "result": result}
 
+    return {"status": "success", "result": result}
 
-    except Exception as e:
-        logging.error(f"Error processing files: {e}")
-        # raise HTTPException(status_code=500, detail="Internal Server Error")
-        return {
-                "status": 400,
-                "message": "Text extraction failed."
-                }
+
+    # except Exception as e:
+    #     logging.error(f"Error processing files: {e}")
+    #     # raise HTTPException(status_code=500, detail="Internal Server Error")
+    #     return {
+    #             "status": 400,
+    #             "message": "Text extraction failed."
+    #             }
     
     

sample.py

@@ -8,22 +8,32 @@ import sys
 # response = requests.get(url)
 
 
-# print("Status Code:", response.status_code)
-# print("Response Text:", response.text)
+
+
 
 # sys.exit()
 
 post_url = "http://localhost:7680/api/aadhar_ocr"
 
+# post_url = "https://auditedge-optimised-ocr.hf.space/api/aadhar_ocr"
+# url = "https://auditedge-optimised-ocr.hf.space/"
+
 # response = requests.get(url)
 
-# print()
-# Define the file pathscd
+
+# print("Status Code:", response.status_code)
+# print("Response Text:", response.text)
+
+
+
+# # print()
+# # Define the file pathscd
 files = {
-    "aadhar_file": open("/Users/javed/Downloads/test_images_folder/aadhar/22.jpg", "rb")
-    # "pan_file": open("/Users/javed/model_one/test_images_pan/6ea33087.jpeg", "rb"),
-    # "cheque_file": open("/Users/javed/model_one/test_images_cheque/0f81678a.jpeg", "rb"),
-    # "gst_file": open("/Users/javed/model_one/test_images_gst/0a52fbcb_page3_image_0.jpg", "rb"),
+    # "aadhar_file": open("/Users/javed/Downloads/test_images_folder/aadhar/22.jpg", "rb")
+    # "pan_file": open("/Users/javed/Downloads/test_images_folder/pan/fcc.14eb7.jpg", "rb"),
+    # "cheque_file": open("/Users/javed/Downloads/test_images_folder/cheque/2.jpeg", "rb"),
+    "gst_file": open("/Users/javed/Downloads/test_images_folder/gst/e.2.pdf", "rb")
+    # "gst_file": open("/Users/javed/Downloads/test_images_folder/gst/x.pdf", "rb")
 }
 
 response = requests.post(post_url, files=files)

utils.py

@@ -46,6 +46,8 @@ class doc_processing:
 
     def scale_img(self):
         
+
+        print("path of file",self.f_path)
         image = Image.open(self.f_path).convert("RGB")
         original_width, original_height = image.size