2D bounding boxes wfo who work job

#2D bounding boxes 

#में आपका स्वागत है

#Translation Guideline

#अनुवाद या प्रतिलिपि जॉब

#Work Job #Work from home

#Work from online

#DSA Loan Partner Application

#Start Pay Online: Apply for Loans and Partner Programs

        

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Your salary or payment is per hour and per munites for all jobs सभी नौकरियों के लिए आपका वेतन या भुगतान प्रति घंटा और प्रति मिनट है
And all jobs are paid weekly. और सभी कार्यो में साप्ताहिक भुगतान मिलता है
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Click and read for more information Payment Terms & Guidelines ??
भुगतान नियम और दिशा निर्देश अधिक जानकारी के लिए क्लिक करें और पढ़ें??

        

Projects -cupcake-oxen-refresher-course-h-itzy-0

प्रोजेक्ट्स -कपकेक-ऑक्सन-रिफ्रेशर-कोर्स-एच-इट्ज़ी-0

Instructions - Updates: निर्देश -Updates:
Please read the following instructions carefully and then proceed to the practice scenarios. कृपया निम्नलिखित निर्देशों को ध्यान से पढ़ें और फिर अभ्यास परिदृश्यों पर आगे बढ़ें।
Update July 2022: Updated minimum Box Size rule and annotation rule for roads. जुलाई 2022 अपडेट: सड़कों के लिए न्यूनतम बॉक्स आकार नियम और एनोटेशन नियम अपडेट किया गया।
Overview अवलोकन
This task involves drawing 2D bounding boxes around individual objects in an image that fall into one of seven categories specified below. The categories include common types of road users. The images being annotated are taken from traffic surveillance cameras monitoring highways.
Here's an example of what you'll be doing in this task.

OPEN IMAGE

All visible Road Users on the main highway must be annotated.
Both moving and stationary/parked objects should be annotated.
Minimum Box Size Rule: If the object is under 15 pixels x 15 pixels for Car, Bus and Commercial truck, you do not need to annotate it, and if the object is under 10 pixels x 10 pixels for Pedestrians, Motorbikes, Bicycles and Emergency Vehicle, you do not need to annotate it. Note that these are very small sizes, and would be rare to leave objects unlabelled. Please use the Ruler tool to get precise measurements.
Do NOT annotate vehicles outside of the main road.
 OPEN IMAGE
If you are uncertained if a car should be label you can use the Rule Tool यदि आप अनिश्चित हैं कि कार पर लेबल लगाया जाना चाहिए या नहीं तो आप नियम उपकरण का उपयोग कर सकते हैं

By pressing "R" on your keyboard the tool should be ready to use, just drag the mouse and measure the car you are uncertain.

आपके कीबोर्ड पर "आर" दबाने से उपकरण उपयोग के लिए तैयार हो जाएगा, बस माउस को खींचें और उस कार को मापें जिसके बारे में आप अनिश्चित हैं।
By pressing "R" again the tool will be deactivated so you can continue working on the task: "R" को दोबारा दबाने पर टूल निष्क्रिय हो जाएगा ताकि आप कार्य पर काम करना जारी रख सकें:
Example of the Rule Tool:  नियम उपकरण का उदाहरण:

OPEN IMAGE

Label Taxonomy

OPEN IMAGE

The chart above shows the taxonomy of class labels. Seven (7) types of common road users have been identified to be labeled in this task. These road users comprise two super-categories: vehicles and vulnerable road users. The vehicles super-category includes five (5) classes: car, bus, truck, motorbike, Emergency Vehicle. The vulnerable road users super-category includes two (2) classes: pedestrian and bicycle.


Label Definitions

A description of each category is provided below. This includes the category definition, edge cases that may be present in a traffic surveillance scene, and examples of the class taken from a traffic surveillance dataset.

Vehicles
Any vehicle driving on the main road should be annotated.

Any vehicle parked on the main road (i.e., parallel parking, disabled vehicles) should be annotated.

Both empty and occupied vehicles should be annotated. Any parked or disabled vehicle without users still needs to be annotated, including motorbikes without a rider.

Vehicles parked in parking lots or driveways should not be annotated.


वाहनों
मुख्य सड़क पर चलने वाले किसी भी वाहन पर टिप्पणी की जानी चाहिए।

मुख्य सड़क पर पार्क किए गए किसी भी वाहन (अर्थात, समानांतर पार्किंग, अक्षम वाहन) पर टिप्पणी की जानी चाहिए।

खाली और कब्जे वाले दोनों वाहनों को एनोटेट किया जाना चाहिए। उपयोगकर्ताओं के बिना पार्क किए गए या अक्षम वाहन को अभी भी एनोटेट करने की आवश्यकता है, जिसमें सवार के बिना मोटरबाइक भी शामिल हैं।

Car
The car category is defined as a four-wheeler that can carry a small number of people. This includes sedans, convertibles, coupes, SUVs, crossovers, jeeps, minivans, light trucks, vans, and most medium pickup truck style trucks (e.g., Chevy Silverado, Ford F-150, Dodge Ram). This category includes taxis and city cars. If a car object is towing a trailer, the trailer must not be included in the car bounding box. Trailers should not be annotated. Examples of correct annotations for cars with trailers can be found under "Special vehicles".

OPEN IMAGE

Figure 1: Examples of Cars from a traffic surveillance dataset
चित्र 1: यातायात निगरानी डेटासेट से कारों के उदाहरण
Bus
The Bus class is defined as a large, elongated communal vehicle used for the transportation of people. This includes small buses like an airport shuttle, municipal articulated buses, and large coach buses.
बस
बस श्रेणी को लोगों के परिवहन के लिए उपयोग किए जाने वाले बड़े, लम्बे सामुदायिक वाहन के रूप में परिभाषित किया गया है। इसमें हवाईअड्डा शटल जैसी छोटी बसें, नगर निगम की आर्टिकुलेटेड बसें और बड़ी कोच बसें शामिल हैं।

OPEN IMAGE

Figure 2: Examples of Buses from a traffic surveillance dataset
चित्र 

Commercial Truck

The commercial truck class is defined as medium and heavy vehicles with separate tractor (cab) and trailer used for the transportation of goods. By the FHWA vehicle category classification, this class includes all Class 6, 7, 8 trucks (“Heavy Trucks”) as well as Class 4, 5 (“Medium Trucks”) with Trailers. This class does not include Class 3, 4, 5 “Medium Trucks” without trailers; pickup truck style trucks are cars and should not be labeled as commercial trucks.

Examples of trucks include moving trucks, large tractor-trailer trucks, dump trucks and other specialized trucks like car carriers. Both the truck’s cab and truck’s trailer(s) should be included in the bounding box. Trucks ("cabs") without a trailer should still be annotated as trucks. Delivery trucks (like FedEx or UPS) and food trucks should also be labeled as trucks.

OPEN IMAGE

Figure 3: Examples of trucks from a traffic surveillance dataset
चित्र 
3: यातायात निगरानी डेटासेट से ट्रकों के उदाहरण

OPEN IMAGE

Note that trailers without a cab should not be annotated. An example where such a case may be seen is a loading dock or other parking area off of the main roadway.
Figure 4. Trailers without a cab should NOT be annotated.
चित्र 

Motorbike


The Motorbike class is defined as a two- or three-wheeled motorized vehicle without a cab. This includes motorcycles, like Harley Davidsons or Suzukis, and motor scooters, like Vespas. Three-wheeled motorbikes (“trikes”) should also be labeled as a motorbike. Electric scooters, like Lime or Spin, and electric bikes are not included in this category. The rider(s) should be included in the motorbike bounding box; they should not be annotated separately as pedestrian(s).

OPEN IMAGE

Figure 5: Examples of motorbikes from a traffic surveillance dataset

Emergency Vehicles

Emergency vehicles are any vehicles used to respond to an incident, which includes police cars, police motorcycles, ambulances, and fire trucks. Emergency vehicles are generally fitted with visual warning devices (i.e., lights) which they use when responding to an emergency. Emergency vehicles both with and without their lights on should be annotated.

OPEN IMAGE

Figure 6: Examples of emergency vehicles from a traffic surveillance dataset.

The table below shows some of the diversity of each class label.

OPEN IMAGE

Vulnerable Road Users
Bicycle
The Bicycle class is defined as a two-wheeled, pedal-driven, single-track vehicle. Both human-powered and electric bicycles fall into this category. Scooters of any kind are not a part of this class. The entire bicycle and human(s) riding the bicycle should be annotated. The human should not be annotated separately as a pedestrian.

OPEN IMAGE

Figure 6: Examples of bicycles from a traffic surveillance dataset
Pedestrians
The Pedestrian class is defined as any person who is not operating a motor vehicle or riding a bicycle. This includes persons who are walking, sitting, or standing. A person riding a small scooter, such as a Lime electric scooter, skateboard, roller skates, etc. who is on the sidewalk should also be annotated as a Pedestrian. The equipment they are using (i.e., skateboard) should be neglected from the bounding box if possible.
Pedestrians often have other items with them. The following rule should be used to determine if any objects with them should be included in the bounding box:

An item, such as a handbag or umbrella, held by a person should be included in the Pedestrian bounding box.

Luggage, carts, and items being pulled or pushed by a person should not be included in the Pedestrian bounding box.

If there is free space between a person and an object they are interacting with, the object should not be included in the bounding box.

OPEN IMAGE

Figure 7: Examples of pedestrians from a traffic surveillance dataset

Special Vehicles

Trailers

Trailers, such as livestock trailers or campers, which are being towed by a car such as an SUV or pickup truck are handled differently than the commercial truck class. Trailers towed by cars should not be annotated. Trailers should not be annotated as “truck” if they are being towed by a car. The car towing the trailer should be annotated as a car. Trailers should not be included inside the bounding box with the car. Trailers being towed by cars are not within the scope of this task.

OPEN IMAGE

Figure 8: Example of correct annotations for cars towing trailers.

चित्र 8: कारों को खींचने वाले ट्रेलरों के लिए सही एनोटेशन का उदाहरण।

Recreational Vehicles (RVs)

RV classification is based on chassis size. RVs can fall into the bus, van, or truck category. The example photos included in the Appendix will be especially helpful in classifying RVs.

RV classification is based on chassis size. RVs can fall into the bus or truck category. However, campers which are being towed by a car should follow the rules presented above for trailers. This means that towed RVs should not be annotated, but the car towing them should be labeled.

Class A RVs should be labeled as a bus.

Class B RVs should be labeled as car.

Class C RVs should be labeled as a truck.

RVs or Campers being towed by a car are trailers and should not be annotated.

RVs or Campers being towed by a Car are trailers and should not be annotated.

आरवी वर्गीकरण चेसिस आकार पर आधारित है। आरवी बस या ट्रक श्रेणी में आ सकते हैं। हालाँकि, जिन कैंपरों को कार द्वारा खींचा जा रहा है, उन्हें ट्रेलरों के लिए ऊपर प्रस्तुत नियमों का पालन करना चाहिए। इसका मतलब यह है कि खींचे गए आरवी को एनोटेट नहीं किया जाना चाहिए, बल्कि उन्हें खींचने वाली कार को लेबल किया जाना चाहिए।

क्लास ए आरवी को बस के रूप में लेबल किया जाना चाहिए।

क्लास बी आरवी को कार के रूप में लेबल किया जाना चाहिए।

क्लास सी आरवी को ट्रक के रूप में लेबल किया जाना चाहिए।

कार द्वारा खींचे जा रहे आरवी या कैंपर ट्रेलर हैं और उन पर टिप्पणी नहीं की जानी चाहिए।

कार द्वारा खींचे जा रहे आरवी या कैंपर ट्रेलर हैं और उन पर टिप्पणी नहीं की जानी चाहिए।


OPEN IMAGE

Tow Trucks and Car Carries

Tow trucks and car carriers should be labeled with their appropriate label (truck or car). Any visible vehicles being towed or carried by the truck should be annotated with a bounding box and their appropriate class as well.

OPEN IMAGE

OPEN IMAGE

Figure 9: Every vehicle being transported by tow truck or car carrier should also be annotated as an object instance itself.
Other Edge Cases
If the class label of a vehicle is ambiguous, such as vehicles in very low-resolution images, the annotator should use their best discretion. A good rule of thumb is to use the relative vehicle size to assign a label. The most common class labels are Car and Commercial Truck.
Small, motorized carts such as golf carts, ATVs, and UTVs should not be labeled.
Fig. 10 Golf Cart
Fig. 11 ATV
Fig. 12 UTV
Unattended scooters, Segways, and other equipment that may be used by pedestrians should not be labeled. If a human is riding a scooter, the human should be labeled as a pedestrian. If a scooter is not being ridden, it should not be labeled.

Any vehicle that is not explicitly defined above should not be left unlabeled. It should still be annotated with a bounding box and given the most appropriate label at the annotator’s discretion. The chassis size of the vehicle is the best indicator of the appropriate class.

A note should be made of the example containing the object, a short description of the object in question, and the label assigned by the annotator. These cases can then be more closely reviewed and additional notes can be added to these guidelines if needed.

Vehicles in the shadow of other vehicles should be annotated, even the portion of the car that is occluded.

पैदल चलने वालों द्वारा इस्तेमाल किए जा सकने वाले लावारिस स्कूटर, सेगवे और अन्य उपकरणों पर लेबल नहीं लगाया जाना चाहिए। यदि कोई व्यक्ति स्कूटर चला रहा है, तो उसे पैदल यात्री के रूप में लेबल किया जाना चाहिए। यदि कोई स्कूटर नहीं चलाया जा रहा है, तो उस पर लेबल नहीं लगाया जाना चाहिए।

कोई भी वाहन जो ऊपर स्पष्ट रूप से परिभाषित नहीं है, उसे लेबल किए बिना नहीं छोड़ा जाना चाहिए। इसे अभी भी एक बाउंडिंग बॉक्स के साथ एनोटेट किया जाना चाहिए और एनोटेटर के विवेक पर सबसे उपयुक्त लेबल दिया जाना चाहिए। वाहन का चेसिस आकार उपयुक्त वर्ग का सबसे अच्छा संकेतक है।

वस्तु वाले उदाहरण, संबंधित वस्तु का संक्षिप्त विवरण और एनोटेटर द्वारा निर्दिष्ट लेबल का एक नोट बनाया जाना चाहिए। इन मामलों की फिर अधिक बारीकी से समीक्षा की जा सकती है और यदि आवश्यक हो तो इन दिशानिर्देशों में अतिरिक्त नोट जोड़े जा सकते हैं।

अन्य वाहनों की छाया में वाहनों को एनोटेट किया जाना चाहिए, यहां तक ​​कि कार के उस हिस्से को भी जो अवरुद्ध है।

OPEN IMAGE

Fig. 13 Vehicle in shadow of other vehicle


Be really careful with commercial trucks, do not misclassify them as buses.

चित्र 13 अन्य वाहन की छाया में वाहन


वाणिज्यिक ट्रकों के साथ बहुत सावधान रहें, उन्हें बसों के रूप में गलत वर्गीकृत न करें।

OPEN IMAGE

Fig. 14 Commercial Truck
Fig. 15 Bus
Bounding Box Guidelines

For this task, individual object instances are annotated with a 2D bounding box. Examples are provided to visualize proper bounding box annotations.

Label every object instance in every image that falls under one of the seven listed categories and has a height and width of at least 15 pixels for Cars, Commercial Trucks or Bus and 10 pixels for Pedestrians, Motorbike, Bicycles and Emergency Vehicles. This means that objects very far from the imager will not be annotated.

OPEN IMAGE

Figure 16: This scene is properly annotated. Notice that very small objects far from the imager are not annotated as they don’t meet the pixel size requirement.

Label the entirety of each object instance. For instance, the mirrors of a vehicle should be included in the bounding box.

OPEN IMAGE

Figure 17: The right image shows the correct bounding box annotation for this truck, which includes the mirror.

Objects that are partially out of frame should still be annotated. The entirety of the object that falls within the frame should be annotated.

OPEN IMAGE

Figure 18: The bounding boxes in this scene show the proper annotation for objects that are partially out of frame.

The bounding box for a partially-occluded object should be drawn as if the entire object is visible. This means that the extent of the object should be estimated, even where the object is occluded.

OPEN IMAGE

Figure 19: Left: incorrect annotation--only the visible portion of the taxi is annotated. Right: correct annotation--the entire taxi, included occluded portions, are annotated.

The images being annotated often have text overlays including timestamps, banners, and watermarks. If an object is occluded by an overlay, it is acceptable to include that portion of the overlay in the bounding box.

OPEN IMAGE

Figure 20: The overlays which occlude a portion of the objects are appropriately included in the bounding boxes of the Cars and Commercial Truck.

Bounding boxes should be drawn tight around each object. The amount of empty space within each bounding box should be minimized. However, bounding boxes should never cut off portions of an object.

चित्र 20: ओवरले जो वस्तुओं के एक हिस्से को अवरुद्ध करते हैं, उन्हें कारों और वाणिज्यिक ट्रक के बाउंडिंग बॉक्स में उचित रूप से शामिल किया गया है।

बाउंडिंग बॉक्स को प्रत्येक वस्तु के चारों ओर कसकर खींचा जाना चाहिए। प्रत्येक बाउंडिंग बॉक्स के भीतर खाली जगह की मात्रा कम से कम होनी चाहिए। हालाँकि, बाउंडिंग बॉक्स को कभी भी किसी वस्तु के हिस्से को नहीं काटना चाहिए।

OPEN IMAGE

Figure 21: The bounding box on the left has too much free space around the truck. The right image shows the correct bounding box annotation.

Each object instance should be annotated with its own bounding box. Multiple objects, even of the same type, should never be labeled together in the same bounding box. It is acceptable for one object that occludes another to be present within the bounding box of the occluded object, but it should also be annotated with its own box and label.

OPEN IMAGE

Figure 22: The right image shows the correct bounding boxes for a group of pedestrians.

Annotations in Challenging Weather and Lighting

Images are captured at all times of day and in all weather conditions. Some images may be challenging to annotate due to low light or low visibility conditions, but they should still be annotated following the guidelines presented above. Examples for how to handle some of these conditions are presented below.

In low light conditions, common challenges include:

Glare from headlights

Objects under heavy glare from headlights at night or the sun during the day should still be annotated. As it can be difficult to distinguish the object class in these cases, one might try to use the relative size of an object to determine the appropriate class.

चित्र 22: दायाँ चित्र पैदल चलने वालों के समूह के लिए सही बाउंडिंग बॉक्स दिखाता है।

चुनौतीपूर्ण मौसम और प्रकाश व्यवस्था में एनोटेशन

छवियाँ दिन के सभी समय और सभी मौसम स्थितियों में कैप्चर की जाती हैं। कुछ छवियों को कम रोशनी या कम दृश्यता की स्थिति के कारण एनोटेट करना चुनौतीपूर्ण हो सकता है, लेकिन फिर भी उन्हें ऊपर दिए गए दिशा-निर्देशों का पालन करते हुए एनोटेट किया जाना चाहिए। इनमें से कुछ स्थितियों को कैसे संभालना है, इसके उदाहरण नीचे दिए गए हैं।

कम रोशनी की स्थिति में, आम चुनौतियों में शामिल हैं:

हेडलाइट्स से चकाचौंध

रात में हेडलाइट्स या दिन के दौरान सूरज की तेज़ चमक वाली वस्तुओं को अभी भी एनोटेट किया जाना चाहिए। चूँकि इन मामलों में ऑब्जेक्ट क्लास को पहचानना मुश्किल हो सकता है, इसलिए कोई व्यक्ति उचित क्लास निर्धारित करने के लिए किसी ऑब्जेक्ट के सापेक्ष आकार का उपयोग करने का प्रयास कर सकता है।

OPEN IMAGE

Figure 23: Bounding boxes are drawn correctly around the full extent of the object, even though it is difficult to distinguish its class due to glare. Because of the relative size, these objects are labeled as cars.

Motion blur of fast-moving objects

Bounding boxes should still be drawn around the extents of the object as before. Motion blur can sometimes make it difficult to distinguish the class of the vehicle, in which case one might try to use the relative size of an object to determine the appropriate class.

OPEN IMAGE

Figure 24: Despite motion blur, the cars pictured below are still annotated with a bounding box drawn around the full extent of the object.

In low visibility conditions from weather events, common challenges include:

Reflections from a wet roadway
Generally, the reflection of headlights should be neglected from the bounding box of an object when possible. In places where it is too difficult to distinguish between glare, reflections, and the object itself, it is okay to include the extents of the lights in the bounding box.

OPEN IMAGE

Figure 25: This scene is properly annotated despite reflections from the wet roadway. The reflections are mostly neglected from the bounding boxes.

Snow that covers the roadway and stopped vehicles

OPEN IMAGE

Figure 26: The image on the left contains three cars, one moving and two disabled. The image on the right is correctly annotated, with bounding boxes drawn around the moving object and both disabled vehicles, including the one covered in snow.

Parking lots and Junkyards (DO NOT ANNOTATE)

OPEN IMAGE

Figure 27: The image on the left contains a parking lot that has many vehicles parked and annotated, this specific parking lot must not be annotated since these vehicles will not move. The image on the right shows how it should look.

Residential Areas

OPEN IMAGE

Figure 28: THe image on the left contains some cars in a Residential Area. These areas should not be labeled. The Image on the right shows no annotations as how it should look

OPEN IMAGE Correct Examples

OPEN IMAGE Common Errors 

        

Tiers challenge

Tiers चुनौती में आपका स्वागत है

a new program built to reward and recognize our top taskers on the platform!

एक नया प्रोग्राम है जिसे प्लेटफॉर्म पर हमारे शीर्ष टास्कर्स को पुरस्कृत करने और पहचानने के लिए बनाया गया है!
Tiers has two different tiers with benefits that will improve your work availability, provide additional customer support, and have faster pay. Tiers के लाभ के साथ दो अलग-अलग स्तर हैं जो आपके कार्य की उपलब्धता में सुधार करेंगे, अतिरिक्त ग्राहक सहायता प्रदान करेंगे, और तेज़ भुगतान करेंगे
Preferred Tier Benefits
• Empty Queue Support
• Faster Customer Support
• Review times are faster than Standard Tier for faster pay
पसंदीदा टियर लाभ
• खाली कतार समर्थन
• तेज़ ग्राहक सहायता
• तेज़ भुगतान के लिए समीक्षा समय मानक टियर की तुलना में तेज़ है
* Elite Tier Benefits
• Access to reserved tasks only for Elite
• Empty Queue Support
• Faster customer support
• Review times are faster than Preferred Tier for faster pay
• Prepayments
• Access to Weekly Bonuses
* एलीट टियर लाभ
• केवल एलीट के लिए आरक्षित कार्यों तक पहुँच
• खाली कतार समर्थन
• तेज़ ग्राहक सहायता
• तेज़ भुगतान के लिए समीक्षा समय पसंदीदा टियर की तुलना में तेज़ है
• पूर्व भुगतान
• साप्ताहिक बोनस तक पहुँच

How do I move to higher Tiers?

मैं ऊँचे स्तर पर कैसे जाऊँ?

नए स्तरों पर पदोन्नत होने के लिए दी गई समय अवधि के भीतर कार्यों को पूरा करके अर्जित करें।

Standard Tier
★Preferred Tier

points 4 in the last 5 weeks

मानक स्तर
★पसंदीदा स्तर
पिछले 5 हफ़्तों में 4 प्वाइंट

★ Preferred Tier
* Elite Tier

points 20 in the last 7 weeks

★पसंदीदा स्तर
* कुलीन स्तर
पिछले 7 हफ़्तों में 20  प्वाइंट

How to Earn points

प्वाइंट कैसे अर्जित करें

Each completed task will give you a certain amount of XP depending on complexity and accuracy. Meet your weekly XP goal to get points

प्रत्येक पूरा किया गया कार्य आपको जटिलता और सटीकता के आधार पर एक निश्चित मात्रा में XP देगा। प्वाइंट प्राप्त करने के लिए अपने साप्ताहिक XP लक्ष्य को पूरा करें

Standard taskers → Earn up to 1 point per week Progress Tracker
480/3.500 XF Dec 6 Dec 14

मानक टास्कर्स → प्रति सप्ताह 1 अंक तक कमाएँ  प्रगति ट्रैकर
480/3.500 XF 6 दिसंबर 14

Preferred & Elite taskers Earn up to 4 points per we
Progress Tracker
11,000/10.000 χ Dec 14

पसंदीदा और एलीट टास्कर्स प्रति सप्ताह 4 अंक तक कमाएँ
प्रगति ट्रैकर
11,000/10.000 χ 14 दिसंबर

How to track progress?

प्रगति को कैसे ट्रैक करें?

o track your progress and know how close you are to being promoted please visit the tasks Tiers tab.

अपनी प्रगति को ट्रैक करने और यह जानने के लिए कि आप पदोन्नत होने के कितने करीब हैं कृपया टास्क टियर टैब पर जाएं।

If you have more questions or want to learn the details of the program please visit the Program Details

        

!Shubh Shuruaat Start Pay ke Sath!

Technical questions or issues?

Please visit the 24/7 Support Portal or email [email protected]

Get Started:"एसपीओं-SPO"

If you have any questions please email us Contact Us or Here

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Additional Information

Knowledge Base:https://crm.startpayonline.com/knowledge-base

तो कृपया मुझसे संपर्क करने में संकोच न करें

🤞🍀

नवीनतम उपलब्ध सर्वेक्षणों तक पहुंचने के लिए रिफ्रेश करें।

 Hindi Audio Recording

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Quality / Acceptance Tips

गुणवत्ता/स्वीकृति युक्तियाँ
"Not meeting the below will lead to project failure and audios rejections."

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